Determining The Role Of Radiation Oncologist Demographic Factors On Segmentation Quality: Insights From A Crowd-Sourced Challenge Using Bayesian Estimation Article Swipe
Kareem A. Wahid
,
Onur Sahin
,
Suprateek Kundu
,
Diana Lin
,
Anthony Alanis
,
Salik Tehami
,
Serageldin Kamel
,
Simon Duke
,
Michael V. Sherer
,
Mathis Ersted Rasmussen
,
Stine Korreman
,
David Fuentes
,
Michael Cislo
,
Benjamin E. Nelms
,
John P. Christodouleas
,
James D. Murphy
,
Abdallah Mohamed
,
Renjie He
,
Mohamed A. Naser
,
Erin F. Gillespie
,
Clifton D. Fuller
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1101/2023.08.30.23294786
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1101/2023.08.30.23294786
BACKGROUND Medical image auto-segmentation is poised to revolutionize radiotherapy workflows. The quality of auto-segmentation training data, primarily derived from clinician observers, is of utmost importance. However, the factors influencing the quality of these clinician-derived segmentations have yet to be fully understood or quantified. Therefore, the purpose of this study was to determine the role of common observer demographic variables on quantitative segmentation performance. METHODS Organ at risk (OAR) and tumor volume segmentations provided by radiation oncologist observers from the Contouring Collaborative for Consensus in Radiation Oncology public dataset were utilized for this study. Segmentations were derived from five separate disease sites comprised of one patient case each: breast, sarcoma, head and neck (H&N), gynecologic (GYN), and gastrointestinal (GI). Segmentation quality was determined on a structure-by-structure basis by comparing the observer segmentations with an expert-derived consensus gold standard primarily using the Dice Similarity Coefficient (DSC); surface DSC was investigated as a secondary metric. Metrics were stratified into binary groups based on previously established structure-specific expert-derived interobserver variability (IOV) cutoffs. Generalized linear mixed-effects models using Markov chain Monte Carlo Bayesian estimation were used to investigate the association between demographic variables and the binarized segmentation quality for each disease site separately. Variables with a highest density interval excluding zero — loosely analogous to frequentist significance — were considered to substantially impact the outcome measure. RESULTS After filtering by practicing radiation oncologists, 574, 110, 452, 112, and 48 structure observations remained for the breast, sarcoma, H&N, GYN, and GI cases, respectively. The median percentage of observations that crossed the expert DSC IOV cutoff when stratified by structure type was 55% and 31% for OARs and tumor volumes, respectively. Bayesian regression analysis revealed tumor category had a substantial negative impact on binarized DSC for the breast (coefficient mean ± standard deviation: –0.97 ± 0.20), sarcoma (–1.04 ± 0.54), H&N (–1.00 ± 0.24), and GI (–2.95 ± 0.98) cases. There were no clear recurring relationships between segmentation quality and demographic variables across the cases, with most variables demonstrating large standard deviations and wide highest density intervals. CONCLUSION Our study highlights substantial uncertainty surrounding conventionally presumed factors influencing segmentation quality. Future studies should investigate additional demographic variables, more patients and imaging modalities, and alternative metrics of segmentation acceptability.
Related Topics
Concepts
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1101/2023.08.30.23294786
- https://www.medrxiv.org/content/medrxiv/early/2023/09/05/2023.08.30.23294786.full.pdf
- OA Status
- green
- References
- 24
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4386315639
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4386315639Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1101/2023.08.30.23294786Digital Object Identifier
- Title
-
Determining The Role Of Radiation Oncologist Demographic Factors On Segmentation Quality: Insights From A Crowd-Sourced Challenge Using Bayesian EstimationWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-08-31Full publication date if available
- Authors
-
Kareem A. Wahid, Onur Sahin, Suprateek Kundu, Diana Lin, Anthony Alanis, Salik Tehami, Serageldin Kamel, Simon Duke, Michael V. Sherer, Mathis Ersted Rasmussen, Stine Korreman, David Fuentes, Michael Cislo, Benjamin E. Nelms, John P. Christodouleas, James D. Murphy, Abdallah Mohamed, Renjie He, Mohamed A. Naser, Erin F. Gillespie, Clifton D. FullerList of authors in order
- Landing page
-
https://doi.org/10.1101/2023.08.30.23294786Publisher landing page
- PDF URL
-
https://www.medrxiv.org/content/medrxiv/early/2023/09/05/2023.08.30.23294786.full.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://www.medrxiv.org/content/medrxiv/early/2023/09/05/2023.08.30.23294786.full.pdfDirect OA link when available
- Concepts
-
Segmentation, Contouring, Medicine, Bayesian probability, Radiation oncologist, Computer science, Artificial intelligence, Medical physics, Radiology, Statistics, Radiation therapy, Mathematics, Computer graphics (images)Top concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- References (count)
-
24Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4386315639 |
|---|---|
| doi | https://doi.org/10.1101/2023.08.30.23294786 |
| ids.doi | https://doi.org/10.1101/2023.08.30.23294786 |
| ids.pmid | https://pubmed.ncbi.nlm.nih.gov/37693394 |
| ids.openalex | https://openalex.org/W4386315639 |
| fwci | 0.0 |
| type | preprint |
| title | Determining The Role Of Radiation Oncologist Demographic Factors On Segmentation Quality: Insights From A Crowd-Sourced Challenge Using Bayesian Estimation |
| biblio.issue | |
| biblio.volume | |
| biblio.last_page | |
| biblio.first_page | |
| topics[0].id | https://openalex.org/T10358 |
| topics[0].field.id | https://openalex.org/fields/31 |
| topics[0].field.display_name | Physics and Astronomy |
| topics[0].score | 0.9998000264167786 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/3108 |
| topics[0].subfield.display_name | Radiation |
| topics[0].display_name | Advanced Radiotherapy Techniques |
| topics[1].id | https://openalex.org/T12422 |
| topics[1].field.id | https://openalex.org/fields/27 |
| topics[1].field.display_name | Medicine |
| topics[1].score | 0.9991999864578247 |
| topics[1].domain.id | https://openalex.org/domains/4 |
| topics[1].domain.display_name | Health Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/2741 |
| topics[1].subfield.display_name | Radiology, Nuclear Medicine and Imaging |
| topics[1].display_name | Radiomics and Machine Learning in Medical Imaging |
| topics[2].id | https://openalex.org/T10844 |
| topics[2].field.id | https://openalex.org/fields/27 |
| topics[2].field.display_name | Medicine |
| topics[2].score | 0.9972000122070312 |
| topics[2].domain.id | https://openalex.org/domains/4 |
| topics[2].domain.display_name | Health Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/2741 |
| topics[2].subfield.display_name | Radiology, Nuclear Medicine and Imaging |
| topics[2].display_name | Radiation Dose and Imaging |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C89600930 |
| concepts[0].level | 2 |
| concepts[0].score | 0.638421893119812 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q1423946 |
| concepts[0].display_name | Segmentation |
| concepts[1].id | https://openalex.org/C2779104521 |
| concepts[1].level | 2 |
| concepts[1].score | 0.6381696462631226 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q23058469 |
| concepts[1].display_name | Contouring |
| concepts[2].id | https://openalex.org/C71924100 |
| concepts[2].level | 0 |
| concepts[2].score | 0.5135231614112854 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q11190 |
| concepts[2].display_name | Medicine |
| concepts[3].id | https://openalex.org/C107673813 |
| concepts[3].level | 2 |
| concepts[3].score | 0.5113381743431091 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q812534 |
| concepts[3].display_name | Bayesian probability |
| concepts[4].id | https://openalex.org/C2780920918 |
| concepts[4].level | 3 |
| concepts[4].score | 0.4343966245651245 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q7280361 |
| concepts[4].display_name | Radiation oncologist |
| concepts[5].id | https://openalex.org/C41008148 |
| concepts[5].level | 0 |
| concepts[5].score | 0.40926897525787354 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[5].display_name | Computer science |
| concepts[6].id | https://openalex.org/C154945302 |
| concepts[6].level | 1 |
| concepts[6].score | 0.4073382616043091 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[6].display_name | Artificial intelligence |
| concepts[7].id | https://openalex.org/C19527891 |
| concepts[7].level | 1 |
| concepts[7].score | 0.38789817690849304 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q1120908 |
| concepts[7].display_name | Medical physics |
| concepts[8].id | https://openalex.org/C126838900 |
| concepts[8].level | 1 |
| concepts[8].score | 0.34284457564353943 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q77604 |
| concepts[8].display_name | Radiology |
| concepts[9].id | https://openalex.org/C105795698 |
| concepts[9].level | 1 |
| concepts[9].score | 0.3300689458847046 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q12483 |
| concepts[9].display_name | Statistics |
| concepts[10].id | https://openalex.org/C509974204 |
| concepts[10].level | 2 |
| concepts[10].score | 0.27590224146842957 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q180507 |
| concepts[10].display_name | Radiation therapy |
| concepts[11].id | https://openalex.org/C33923547 |
| concepts[11].level | 0 |
| concepts[11].score | 0.2135116457939148 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[11].display_name | Mathematics |
| concepts[12].id | https://openalex.org/C121684516 |
| concepts[12].level | 1 |
| concepts[12].score | 0.0 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q7600677 |
| concepts[12].display_name | Computer graphics (images) |
| keywords[0].id | https://openalex.org/keywords/segmentation |
| keywords[0].score | 0.638421893119812 |
| keywords[0].display_name | Segmentation |
| keywords[1].id | https://openalex.org/keywords/contouring |
| keywords[1].score | 0.6381696462631226 |
| keywords[1].display_name | Contouring |
| keywords[2].id | https://openalex.org/keywords/medicine |
| keywords[2].score | 0.5135231614112854 |
| keywords[2].display_name | Medicine |
| keywords[3].id | https://openalex.org/keywords/bayesian-probability |
| keywords[3].score | 0.5113381743431091 |
| keywords[3].display_name | Bayesian probability |
| keywords[4].id | https://openalex.org/keywords/radiation-oncologist |
| keywords[4].score | 0.4343966245651245 |
| keywords[4].display_name | Radiation oncologist |
| keywords[5].id | https://openalex.org/keywords/computer-science |
| keywords[5].score | 0.40926897525787354 |
| keywords[5].display_name | Computer science |
| keywords[6].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[6].score | 0.4073382616043091 |
| keywords[6].display_name | Artificial intelligence |
| keywords[7].id | https://openalex.org/keywords/medical-physics |
| keywords[7].score | 0.38789817690849304 |
| keywords[7].display_name | Medical physics |
| keywords[8].id | https://openalex.org/keywords/radiology |
| keywords[8].score | 0.34284457564353943 |
| keywords[8].display_name | Radiology |
| keywords[9].id | https://openalex.org/keywords/statistics |
| keywords[9].score | 0.3300689458847046 |
| keywords[9].display_name | Statistics |
| keywords[10].id | https://openalex.org/keywords/radiation-therapy |
| keywords[10].score | 0.27590224146842957 |
| keywords[10].display_name | Radiation therapy |
| keywords[11].id | https://openalex.org/keywords/mathematics |
| keywords[11].score | 0.2135116457939148 |
| keywords[11].display_name | Mathematics |
| language | en |
| locations[0].id | doi:10.1101/2023.08.30.23294786 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S4306402567 |
| locations[0].source.issn | |
| locations[0].source.type | repository |
| locations[0].source.is_oa | False |
| locations[0].source.issn_l | |
| locations[0].source.is_core | False |
| locations[0].source.is_in_doaj | False |
| locations[0].source.display_name | bioRxiv (Cold Spring Harbor Laboratory) |
| locations[0].source.host_organization | https://openalex.org/I2750212522 |
| locations[0].source.host_organization_name | Cold Spring Harbor Laboratory |
| locations[0].source.host_organization_lineage | https://openalex.org/I2750212522 |
| locations[0].license | cc-by |
| locations[0].pdf_url | https://www.medrxiv.org/content/medrxiv/early/2023/09/05/2023.08.30.23294786.full.pdf |
| locations[0].version | acceptedVersion |
| locations[0].raw_type | posted-content |
| locations[0].license_id | https://openalex.org/licenses/cc-by |
| locations[0].is_accepted | True |
| locations[0].is_published | False |
| locations[0].raw_source_name | |
| locations[0].landing_page_url | https://doi.org/10.1101/2023.08.30.23294786 |
| locations[1].id | pmid:37693394 |
| locations[1].is_oa | False |
| locations[1].source.id | https://openalex.org/S4306525036 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | False |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | PubMed |
| locations[1].source.host_organization | https://openalex.org/I1299303238 |
| locations[1].source.host_organization_name | National Institutes of Health |
| locations[1].source.host_organization_lineage | https://openalex.org/I1299303238 |
| locations[1].license | |
| locations[1].pdf_url | |
| locations[1].version | publishedVersion |
| locations[1].raw_type | |
| locations[1].license_id | |
| locations[1].is_accepted | True |
| locations[1].is_published | True |
| locations[1].raw_source_name | medRxiv : the preprint server for health sciences |
| locations[1].landing_page_url | https://pubmed.ncbi.nlm.nih.gov/37693394 |
| locations[2].id | pmh:oai:pubmedcentral.nih.gov:10491357 |
| locations[2].is_oa | True |
| locations[2].source.id | https://openalex.org/S2764455111 |
| locations[2].source.issn | |
| locations[2].source.type | repository |
| locations[2].source.is_oa | False |
| locations[2].source.issn_l | |
| locations[2].source.is_core | False |
| locations[2].source.is_in_doaj | False |
| locations[2].source.display_name | PubMed Central |
| locations[2].source.host_organization | https://openalex.org/I1299303238 |
| locations[2].source.host_organization_name | National Institutes of Health |
| locations[2].source.host_organization_lineage | https://openalex.org/I1299303238 |
| locations[2].license | cc-by |
| locations[2].pdf_url | https://pmc.ncbi.nlm.nih.gov/articles/PMC10491357/pdf/nihpp-2023.08.30.23294786v2.pdf |
| locations[2].version | submittedVersion |
| locations[2].raw_type | Text |
| locations[2].license_id | https://openalex.org/licenses/cc-by |
| locations[2].is_accepted | False |
| locations[2].is_published | False |
| locations[2].raw_source_name | medRxiv |
| locations[2].landing_page_url | https://www.ncbi.nlm.nih.gov/pmc/articles/10491357 |
| locations[3].id | pmh:oai:pure.atira.dk:publications/b3f5e579-1041-40ca-92a9-4b06e6002243 |
| locations[3].is_oa | False |
| locations[3].source.id | https://openalex.org/S4306400216 |
| locations[3].source.issn | |
| locations[3].source.type | repository |
| locations[3].source.is_oa | False |
| locations[3].source.issn_l | |
| locations[3].source.is_core | False |
| locations[3].source.is_in_doaj | False |
| locations[3].source.display_name | Research Portal (King's College London) |
| locations[3].source.host_organization | https://openalex.org/I183935753 |
| locations[3].source.host_organization_name | King's College London |
| locations[3].source.host_organization_lineage | https://openalex.org/I183935753 |
| locations[3].license | |
| locations[3].pdf_url | |
| locations[3].version | submittedVersion |
| locations[3].raw_type | workingPaper |
| locations[3].license_id | |
| locations[3].is_accepted | False |
| locations[3].is_published | False |
| locations[3].raw_source_name | Wahid, K A, Sahin, O, Kundu, S, Lin, D, Alanis, A, Tehami, S, Kamel, S, Duke, S, Sherer, M V, Rasmussen, M, Korreman, S, Fuentes, D, Cislo, M, Nelms, B E, Christodouleas, J P, Murphy, J D, Mohamed, A S R, He, R, Naser, M A, Gillespie, E F & Fuller, C D 2023 'Determining The Role Of Radiation Oncologist Demographic Factors On Segmentation Quality : Insights From A Crowd-Sourced Challenge Using Bayesian Estimation' medRxiv. https://doi.org/10.1101/2023.08.30.23294786 |
| locations[3].landing_page_url | https://pure.au.dk/portal/en/publications/b3f5e579-1041-40ca-92a9-4b06e6002243 |
| indexed_in | crossref, pubmed |
| authorships[0].author.id | https://openalex.org/A5020727877 |
| authorships[0].author.orcid | https://orcid.org/0000-0002-0503-0175 |
| authorships[0].author.display_name | Kareem A. Wahid |
| authorships[0].countries | US |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I1343551460 |
| authorships[0].affiliations[0].raw_affiliation_string | Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA |
| authorships[0].affiliations[1].institution_ids | https://openalex.org/I1343551460 |
| authorships[0].affiliations[1].raw_affiliation_string | Deprtment of Rdition Oncology, The University of Texs MD Anderson Cncer Center, Houston, Texs, USA |
| authorships[0].institutions[0].id | https://openalex.org/I1343551460 |
| authorships[0].institutions[0].ror | https://ror.org/04twxam07 |
| authorships[0].institutions[0].type | healthcare |
| authorships[0].institutions[0].lineage | https://openalex.org/I1343551460 |
| authorships[0].institutions[0].country_code | US |
| authorships[0].institutions[0].display_name | The University of Texas MD Anderson Cancer Center |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Kareem A. Wahid |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA, Deprtment of Rdition Oncology, The University of Texs MD Anderson Cncer Center, Houston, Texs, USA |
| authorships[1].author.id | https://openalex.org/A5012275164 |
| authorships[1].author.orcid | https://orcid.org/0000-0003-2191-5659 |
| authorships[1].author.display_name | Onur Sahin |
| authorships[1].countries | US |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I1343551460 |
| authorships[1].affiliations[0].raw_affiliation_string | Deprtment of Rdition Oncology, The University of Texs MD Anderson Cncer Center, Houston, Texs, USA |
| authorships[1].institutions[0].id | https://openalex.org/I1343551460 |
| authorships[1].institutions[0].ror | https://ror.org/04twxam07 |
| authorships[1].institutions[0].type | healthcare |
| authorships[1].institutions[0].lineage | https://openalex.org/I1343551460 |
| authorships[1].institutions[0].country_code | US |
| authorships[1].institutions[0].display_name | The University of Texas MD Anderson Cancer Center |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Onur Sahin |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | Deprtment of Rdition Oncology, The University of Texs MD Anderson Cncer Center, Houston, Texs, USA |
| authorships[2].author.id | https://openalex.org/A5083350924 |
| authorships[2].author.orcid | https://orcid.org/0000-0002-1767-4875 |
| authorships[2].author.display_name | Suprateek Kundu |
| authorships[2].countries | US |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I1343551460 |
| authorships[2].affiliations[0].raw_affiliation_string | Department of Biostatistis, The University of Texas MD Anderson Caner Center, Houston, Texas, USA |
| authorships[2].institutions[0].id | https://openalex.org/I1343551460 |
| authorships[2].institutions[0].ror | https://ror.org/04twxam07 |
| authorships[2].institutions[0].type | healthcare |
| authorships[2].institutions[0].lineage | https://openalex.org/I1343551460 |
| authorships[2].institutions[0].country_code | US |
| authorships[2].institutions[0].display_name | The University of Texas MD Anderson Cancer Center |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Suprateek Kundu |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | Department of Biostatistis, The University of Texas MD Anderson Caner Center, Houston, Texas, USA |
| authorships[3].author.id | https://openalex.org/A5007526835 |
| authorships[3].author.orcid | https://orcid.org/0000-0002-1173-0725 |
| authorships[3].author.display_name | Diana Lin |
| authorships[3].countries | US |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I1334819555 |
| authorships[3].affiliations[0].raw_affiliation_string | Department of Raiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY |
| authorships[3].institutions[0].id | https://openalex.org/I1334819555 |
| authorships[3].institutions[0].ror | https://ror.org/02yrq0923 |
| authorships[3].institutions[0].type | healthcare |
| authorships[3].institutions[0].lineage | https://openalex.org/I1334819555 |
| authorships[3].institutions[0].country_code | US |
| authorships[3].institutions[0].display_name | Memorial Sloan Kettering Cancer Center |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Diana Lin |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | Department of Raiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY |
| authorships[4].author.id | https://openalex.org/A5049362422 |
| authorships[4].author.orcid | https://orcid.org/0000-0002-9722-7580 |
| authorships[4].author.display_name | Anthony Alanis |
| authorships[4].countries | US |
| authorships[4].affiliations[0].institution_ids | https://openalex.org/I1343551460 |
| authorships[4].affiliations[0].raw_affiliation_string | Deprtment of Rdition Oncology, The University of Texs MD Anderson Cncer Center, Houston, Texs, USA |
| authorships[4].institutions[0].id | https://openalex.org/I1343551460 |
| authorships[4].institutions[0].ror | https://ror.org/04twxam07 |
| authorships[4].institutions[0].type | healthcare |
| authorships[4].institutions[0].lineage | https://openalex.org/I1343551460 |
| authorships[4].institutions[0].country_code | US |
| authorships[4].institutions[0].display_name | The University of Texas MD Anderson Cancer Center |
| authorships[4].author_position | middle |
| authorships[4].raw_author_name | Anthony Alanis |
| authorships[4].is_corresponding | False |
| authorships[4].raw_affiliation_strings | Deprtment of Rdition Oncology, The University of Texs MD Anderson Cncer Center, Houston, Texs, USA |
| authorships[5].author.id | https://openalex.org/A5092723379 |
| authorships[5].author.orcid | |
| authorships[5].author.display_name | Salik Tehami |
| authorships[5].countries | US |
| authorships[5].affiliations[0].institution_ids | https://openalex.org/I1343551460 |
| authorships[5].affiliations[0].raw_affiliation_string | Deprtment of Rdition Oncology, The University of Texs MD Anderson Cncer Center, Houston, Texs, USA |
| authorships[5].institutions[0].id | https://openalex.org/I1343551460 |
| authorships[5].institutions[0].ror | https://ror.org/04twxam07 |
| authorships[5].institutions[0].type | healthcare |
| authorships[5].institutions[0].lineage | https://openalex.org/I1343551460 |
| authorships[5].institutions[0].country_code | US |
| authorships[5].institutions[0].display_name | The University of Texas MD Anderson Cancer Center |
| authorships[5].author_position | middle |
| authorships[5].raw_author_name | Salik Tehami |
| authorships[5].is_corresponding | False |
| authorships[5].raw_affiliation_strings | Deprtment of Rdition Oncology, The University of Texs MD Anderson Cncer Center, Houston, Texs, USA |
| authorships[6].author.id | https://openalex.org/A5007574242 |
| authorships[6].author.orcid | https://orcid.org/0000-0002-0046-4337 |
| authorships[6].author.display_name | Serageldin Kamel |
| authorships[6].countries | US |
| authorships[6].affiliations[0].institution_ids | https://openalex.org/I1343551460 |
| authorships[6].affiliations[0].raw_affiliation_string | Deprtment of Rdition Oncology, The University of Texs MD Anderson Cncer Center, Houston, Texs, USA |
| authorships[6].institutions[0].id | https://openalex.org/I1343551460 |
| authorships[6].institutions[0].ror | https://ror.org/04twxam07 |
| authorships[6].institutions[0].type | healthcare |
| authorships[6].institutions[0].lineage | https://openalex.org/I1343551460 |
| authorships[6].institutions[0].country_code | US |
| authorships[6].institutions[0].display_name | The University of Texas MD Anderson Cancer Center |
| authorships[6].author_position | middle |
| authorships[6].raw_author_name | Serageldin Kamel |
| authorships[6].is_corresponding | False |
| authorships[6].raw_affiliation_strings | Deprtment of Rdition Oncology, The University of Texs MD Anderson Cncer Center, Houston, Texs, USA |
| authorships[7].author.id | https://openalex.org/A5065804462 |
| authorships[7].author.orcid | |
| authorships[7].author.display_name | Simon Duke |
| authorships[7].affiliations[0].raw_affiliation_string | Dpartmnt of Radiation Oncology, Cambridg Univrsity Hospitals, Cambridg, UK |
| authorships[7].author_position | middle |
| authorships[7].raw_author_name | Simon Duke |
| authorships[7].is_corresponding | False |
| authorships[7].raw_affiliation_strings | Dpartmnt of Radiation Oncology, Cambridg Univrsity Hospitals, Cambridg, UK |
| authorships[8].author.id | https://openalex.org/A5030086472 |
| authorships[8].author.orcid | https://orcid.org/0000-0002-4439-7906 |
| authorships[8].author.display_name | Michael V. Sherer |
| authorships[8].affiliations[0].raw_affiliation_string | Department o Radiation Medicine and Applied Sciences, University o Caliornia San Diego, La Jolla, CA, USA |
| authorships[8].author_position | middle |
| authorships[8].raw_author_name | Michael V. Sherer |
| authorships[8].is_corresponding | False |
| authorships[8].raw_affiliation_strings | Department o Radiation Medicine and Applied Sciences, University o Caliornia San Diego, La Jolla, CA, USA |
| authorships[9].author.id | https://openalex.org/A5111248548 |
| authorships[9].author.orcid | |
| authorships[9].author.display_name | Mathis Ersted Rasmussen |
| authorships[9].countries | DK |
| authorships[9].affiliations[0].institution_ids | https://openalex.org/I2802335433 |
| authorships[9].affiliations[0].raw_affiliation_string | Department of Oncoloy, Aarhus University Hospital, Denmark |
| authorships[9].institutions[0].id | https://openalex.org/I2802335433 |
| authorships[9].institutions[0].ror | https://ror.org/040r8fr65 |
| authorships[9].institutions[0].type | healthcare |
| authorships[9].institutions[0].lineage | https://openalex.org/I2802335433 |
| authorships[9].institutions[0].country_code | DK |
| authorships[9].institutions[0].display_name | Aarhus University Hospital |
| authorships[9].author_position | middle |
| authorships[9].raw_author_name | Mathis Rasmussen |
| authorships[9].is_corresponding | False |
| authorships[9].raw_affiliation_strings | Department of Oncoloy, Aarhus University Hospital, Denmark |
| authorships[10].author.id | https://openalex.org/A5027977681 |
| authorships[10].author.orcid | https://orcid.org/0000-0002-3523-382X |
| authorships[10].author.display_name | Stine Korreman |
| authorships[10].countries | DK |
| authorships[10].affiliations[0].institution_ids | https://openalex.org/I2802335433 |
| authorships[10].affiliations[0].raw_affiliation_string | Department of Oncoloy, Aarhus University Hospital, Denmark |
| authorships[10].institutions[0].id | https://openalex.org/I2802335433 |
| authorships[10].institutions[0].ror | https://ror.org/040r8fr65 |
| authorships[10].institutions[0].type | healthcare |
| authorships[10].institutions[0].lineage | https://openalex.org/I2802335433 |
| authorships[10].institutions[0].country_code | DK |
| authorships[10].institutions[0].display_name | Aarhus University Hospital |
| authorships[10].author_position | middle |
| authorships[10].raw_author_name | Stine Korreman |
| authorships[10].is_corresponding | False |
| authorships[10].raw_affiliation_strings | Department of Oncoloy, Aarhus University Hospital, Denmark |
| authorships[11].author.id | https://openalex.org/A5030148633 |
| authorships[11].author.orcid | https://orcid.org/0000-0002-2572-6962 |
| authorships[11].author.display_name | David Fuentes |
| authorships[11].countries | US |
| authorships[11].affiliations[0].institution_ids | https://openalex.org/I1343551460 |
| authorships[11].affiliations[0].raw_affiliation_string | Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA |
| authorships[11].institutions[0].id | https://openalex.org/I1343551460 |
| authorships[11].institutions[0].ror | https://ror.org/04twxam07 |
| authorships[11].institutions[0].type | healthcare |
| authorships[11].institutions[0].lineage | https://openalex.org/I1343551460 |
| authorships[11].institutions[0].country_code | US |
| authorships[11].institutions[0].display_name | The University of Texas MD Anderson Cancer Center |
| authorships[11].author_position | middle |
| authorships[11].raw_author_name | David Fuentes |
| authorships[11].is_corresponding | False |
| authorships[11].raw_affiliation_strings | Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA |
| authorships[12].author.id | https://openalex.org/A5028494808 |
| authorships[12].author.orcid | https://orcid.org/0000-0002-5880-2802 |
| authorships[12].author.display_name | Michael Cislo |
| authorships[12].countries | US |
| authorships[12].affiliations[0].institution_ids | https://openalex.org/I1334819555 |
| authorships[12].affiliations[0].raw_affiliation_string | Department of Raiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY |
| authorships[12].institutions[0].id | https://openalex.org/I1334819555 |
| authorships[12].institutions[0].ror | https://ror.org/02yrq0923 |
| authorships[12].institutions[0].type | healthcare |
| authorships[12].institutions[0].lineage | https://openalex.org/I1334819555 |
| authorships[12].institutions[0].country_code | US |
| authorships[12].institutions[0].display_name | Memorial Sloan Kettering Cancer Center |
| authorships[12].author_position | middle |
| authorships[12].raw_author_name | Michael Cislo |
| authorships[12].is_corresponding | False |
| authorships[12].raw_affiliation_strings | Department of Raiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY |
| authorships[13].author.id | https://openalex.org/A5108707889 |
| authorships[13].author.orcid | |
| authorships[13].author.display_name | Benjamin E. Nelms |
| authorships[13].affiliations[0].raw_affiliation_string | Canis Lupus, LLC, Merrimac, WI, USA |
| authorships[13].author_position | middle |
| authorships[13].raw_author_name | Benjamin E. Nelms |
| authorships[13].is_corresponding | False |
| authorships[13].raw_affiliation_strings | Canis Lupus, LLC, Merrimac, WI, USA |
| authorships[14].author.id | https://openalex.org/A5040742979 |
| authorships[14].author.orcid | https://orcid.org/0000-0001-5061-2038 |
| authorships[14].author.display_name | John P. Christodouleas |
| authorships[14].countries | US |
| authorships[14].affiliations[0].institution_ids | https://openalex.org/I4210148054 |
| authorships[14].affiliations[0].raw_affiliation_string | Elekta, Atlanta, GA, USA |
| authorships[14].affiliations[1].raw_affiliation_string | Department of Radaton Oncology, The Unversty of Pennsylvana Cancer Center, Phladelpha, PA, USA |
| authorships[14].institutions[0].id | https://openalex.org/I4210148054 |
| authorships[14].institutions[0].ror | https://ror.org/03me50s15 |
| authorships[14].institutions[0].type | company |
| authorships[14].institutions[0].lineage | https://openalex.org/I4210123750, https://openalex.org/I4210148054 |
| authorships[14].institutions[0].country_code | US |
| authorships[14].institutions[0].display_name | Elekta (United States) |
| authorships[14].author_position | middle |
| authorships[14].raw_author_name | John P. Christodouleas |
| authorships[14].is_corresponding | False |
| authorships[14].raw_affiliation_strings | Department of Radaton Oncology, The Unversty of Pennsylvana Cancer Center, Phladelpha, PA, USA, Elekta, Atlanta, GA, USA |
| authorships[15].author.id | https://openalex.org/A5042215564 |
| authorships[15].author.orcid | https://orcid.org/0009-0008-1719-5111 |
| authorships[15].author.display_name | James D. Murphy |
| authorships[15].affiliations[0].raw_affiliation_string | Department o Radiation Medicine and Applied Sciences, University o Caliornia San Diego, La Jolla, CA, USA |
| authorships[15].author_position | middle |
| authorships[15].raw_author_name | James D. Murphy |
| authorships[15].is_corresponding | False |
| authorships[15].raw_affiliation_strings | Department o Radiation Medicine and Applied Sciences, University o Caliornia San Diego, La Jolla, CA, USA |
| authorships[16].author.id | https://openalex.org/A5100363961 |
| authorships[16].author.orcid | https://orcid.org/0000-0003-2064-7613 |
| authorships[16].author.display_name | Abdallah Mohamed |
| authorships[16].countries | US |
| authorships[16].affiliations[0].institution_ids | https://openalex.org/I1343551460 |
| authorships[16].affiliations[0].raw_affiliation_string | Deprtment of Rdition Oncology, The University of Texs MD Anderson Cncer Center, Houston, Texs, USA |
| authorships[16].institutions[0].id | https://openalex.org/I1343551460 |
| authorships[16].institutions[0].ror | https://ror.org/04twxam07 |
| authorships[16].institutions[0].type | healthcare |
| authorships[16].institutions[0].lineage | https://openalex.org/I1343551460 |
| authorships[16].institutions[0].country_code | US |
| authorships[16].institutions[0].display_name | The University of Texas MD Anderson Cancer Center |
| authorships[16].author_position | middle |
| authorships[16].raw_author_name | Abdallah S. R. Mohamed |
| authorships[16].is_corresponding | False |
| authorships[16].raw_affiliation_strings | Deprtment of Rdition Oncology, The University of Texs MD Anderson Cncer Center, Houston, Texs, USA |
| authorships[17].author.id | https://openalex.org/A5005504553 |
| authorships[17].author.orcid | https://orcid.org/0000-0001-9166-6286 |
| authorships[17].author.display_name | Renjie He |
| authorships[17].countries | US |
| authorships[17].affiliations[0].institution_ids | https://openalex.org/I1343551460 |
| authorships[17].affiliations[0].raw_affiliation_string | Deprtment of Rdition Oncology, The University of Texs MD Anderson Cncer Center, Houston, Texs, USA |
| authorships[17].institutions[0].id | https://openalex.org/I1343551460 |
| authorships[17].institutions[0].ror | https://ror.org/04twxam07 |
| authorships[17].institutions[0].type | healthcare |
| authorships[17].institutions[0].lineage | https://openalex.org/I1343551460 |
| authorships[17].institutions[0].country_code | US |
| authorships[17].institutions[0].display_name | The University of Texas MD Anderson Cancer Center |
| authorships[17].author_position | middle |
| authorships[17].raw_author_name | Renjie He |
| authorships[17].is_corresponding | False |
| authorships[17].raw_affiliation_strings | Deprtment of Rdition Oncology, The University of Texs MD Anderson Cncer Center, Houston, Texs, USA |
| authorships[18].author.id | https://openalex.org/A5050527536 |
| authorships[18].author.orcid | https://orcid.org/0000-0003-1020-4966 |
| authorships[18].author.display_name | Mohamed A. Naser |
| authorships[18].countries | US |
| authorships[18].affiliations[0].institution_ids | https://openalex.org/I1343551460 |
| authorships[18].affiliations[0].raw_affiliation_string | Deprtment of Rdition Oncology, The University of Texs MD Anderson Cncer Center, Houston, Texs, USA |
| authorships[18].institutions[0].id | https://openalex.org/I1343551460 |
| authorships[18].institutions[0].ror | https://ror.org/04twxam07 |
| authorships[18].institutions[0].type | healthcare |
| authorships[18].institutions[0].lineage | https://openalex.org/I1343551460 |
| authorships[18].institutions[0].country_code | US |
| authorships[18].institutions[0].display_name | The University of Texas MD Anderson Cancer Center |
| authorships[18].author_position | middle |
| authorships[18].raw_author_name | Mohammed A. Naser |
| authorships[18].is_corresponding | False |
| authorships[18].raw_affiliation_strings | Deprtment of Rdition Oncology, The University of Texs MD Anderson Cncer Center, Houston, Texs, USA |
| authorships[19].author.id | https://openalex.org/A5056322583 |
| authorships[19].author.orcid | https://orcid.org/0000-0002-1386-1542 |
| authorships[19].author.display_name | Erin F. Gillespie |
| authorships[19].countries | US |
| authorships[19].affiliations[0].institution_ids | https://openalex.org/I4210089486 |
| authorships[19].affiliations[0].raw_affiliation_string | Fred Hutchinson Cancer Center, Seattle, WA, USA |
| authorships[19].institutions[0].id | https://openalex.org/I4210089486 |
| authorships[19].institutions[0].ror | https://ror.org/007ps6h72 |
| authorships[19].institutions[0].type | nonprofit |
| authorships[19].institutions[0].lineage | https://openalex.org/I4210089486 |
| authorships[19].institutions[0].country_code | US |
| authorships[19].institutions[0].display_name | Fred Hutch Cancer Center |
| authorships[19].author_position | middle |
| authorships[19].raw_author_name | Erin F. Gillespie |
| authorships[19].is_corresponding | True |
| authorships[19].raw_affiliation_strings | Fred Hutchinson Cancer Center, Seattle, WA, USA |
| authorships[20].author.id | https://openalex.org/A5052234283 |
| authorships[20].author.orcid | https://orcid.org/0000-0002-5264-3994 |
| authorships[20].author.display_name | Clifton D. Fuller |
| authorships[20].countries | US |
| authorships[20].affiliations[0].institution_ids | https://openalex.org/I1343551460 |
| authorships[20].affiliations[0].raw_affiliation_string | Deprtment of Rdition Oncology, The University of Texs MD Anderson Cncer Center, Houston, Texs, USA |
| authorships[20].institutions[0].id | https://openalex.org/I1343551460 |
| authorships[20].institutions[0].ror | https://ror.org/04twxam07 |
| authorships[20].institutions[0].type | healthcare |
| authorships[20].institutions[0].lineage | https://openalex.org/I1343551460 |
| authorships[20].institutions[0].country_code | US |
| authorships[20].institutions[0].display_name | The University of Texas MD Anderson Cancer Center |
| authorships[20].author_position | last |
| authorships[20].raw_author_name | Clifton D. Fuller |
| authorships[20].is_corresponding | True |
| authorships[20].raw_affiliation_strings | Deprtment of Rdition Oncology, The University of Texs MD Anderson Cncer Center, Houston, Texs, USA |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://www.medrxiv.org/content/medrxiv/early/2023/09/05/2023.08.30.23294786.full.pdf |
| open_access.oa_status | green |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Determining The Role Of Radiation Oncologist Demographic Factors On Segmentation Quality: Insights From A Crowd-Sourced Challenge Using Bayesian Estimation |
| has_fulltext | True |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T10358 |
| primary_topic.field.id | https://openalex.org/fields/31 |
| primary_topic.field.display_name | Physics and Astronomy |
| primary_topic.score | 0.9998000264167786 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/3108 |
| primary_topic.subfield.display_name | Radiation |
| primary_topic.display_name | Advanced Radiotherapy Techniques |
| related_works | https://openalex.org/W2167401887, https://openalex.org/W2885048735, https://openalex.org/W2018199237, https://openalex.org/W2033501351, https://openalex.org/W1548510492, https://openalex.org/W2058308393, https://openalex.org/W4281552652, https://openalex.org/W2537862542, https://openalex.org/W2642912725, https://openalex.org/W2006014249 |
| cited_by_count | 0 |
| locations_count | 4 |
| best_oa_location.id | doi:10.1101/2023.08.30.23294786 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S4306402567 |
| best_oa_location.source.issn | |
| best_oa_location.source.type | repository |
| best_oa_location.source.is_oa | False |
| best_oa_location.source.issn_l | |
| best_oa_location.source.is_core | False |
| best_oa_location.source.is_in_doaj | False |
| best_oa_location.source.display_name | bioRxiv (Cold Spring Harbor Laboratory) |
| best_oa_location.source.host_organization | https://openalex.org/I2750212522 |
| best_oa_location.source.host_organization_name | Cold Spring Harbor Laboratory |
| best_oa_location.source.host_organization_lineage | https://openalex.org/I2750212522 |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | https://www.medrxiv.org/content/medrxiv/early/2023/09/05/2023.08.30.23294786.full.pdf |
| best_oa_location.version | acceptedVersion |
| best_oa_location.raw_type | posted-content |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | False |
| best_oa_location.raw_source_name | |
| best_oa_location.landing_page_url | https://doi.org/10.1101/2023.08.30.23294786 |
| primary_location.id | doi:10.1101/2023.08.30.23294786 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S4306402567 |
| primary_location.source.issn | |
| primary_location.source.type | repository |
| primary_location.source.is_oa | False |
| primary_location.source.issn_l | |
| primary_location.source.is_core | False |
| primary_location.source.is_in_doaj | False |
| primary_location.source.display_name | bioRxiv (Cold Spring Harbor Laboratory) |
| primary_location.source.host_organization | https://openalex.org/I2750212522 |
| primary_location.source.host_organization_name | Cold Spring Harbor Laboratory |
| primary_location.source.host_organization_lineage | https://openalex.org/I2750212522 |
| primary_location.license | cc-by |
| primary_location.pdf_url | https://www.medrxiv.org/content/medrxiv/early/2023/09/05/2023.08.30.23294786.full.pdf |
| primary_location.version | acceptedVersion |
| primary_location.raw_type | posted-content |
| primary_location.license_id | https://openalex.org/licenses/cc-by |
| primary_location.is_accepted | True |
| primary_location.is_published | False |
| primary_location.raw_source_name | |
| primary_location.landing_page_url | https://doi.org/10.1101/2023.08.30.23294786 |
| publication_date | 2023-08-31 |
| publication_year | 2023 |
| referenced_works | https://openalex.org/W3160604201, https://openalex.org/W4205888790, https://openalex.org/W4319591412, https://openalex.org/W4378173261, https://openalex.org/W2513503320, https://openalex.org/W2226272315, https://openalex.org/W1960881728, https://openalex.org/W4353063369, https://openalex.org/W2814789634, https://openalex.org/W2148347694, https://openalex.org/W3130548058, https://openalex.org/W3180629942, https://openalex.org/W2128088446, https://openalex.org/W2910719176, https://openalex.org/W2968619018, https://openalex.org/W4319161247, https://openalex.org/W4210520314, https://openalex.org/W2602656607, https://openalex.org/W4281614967, https://openalex.org/W2346563756, https://openalex.org/W2751762560, https://openalex.org/W3017386006, https://openalex.org/W4207071932, https://openalex.org/W4387643081 |
| referenced_works_count | 24 |
| abstract_inverted_index.a | 124, 150, 201, 282 |
| abstract_inverted_index.48 | 234 |
| abstract_inverted_index.GI | 245, 309 |
| abstract_inverted_index.an | 133 |
| abstract_inverted_index.as | 149 |
| abstract_inverted_index.at | 66 |
| abstract_inverted_index.be | 39 |
| abstract_inverted_index.by | 74, 127, 225, 262 |
| abstract_inverted_index.in | 84 |
| abstract_inverted_index.is | 5, 22 |
| abstract_inverted_index.no | 316 |
| abstract_inverted_index.of | 13, 23, 32, 47, 55, 103, 251, 369 |
| abstract_inverted_index.on | 60, 123, 160, 286 |
| abstract_inverted_index.or | 42 |
| abstract_inverted_index.to | 7, 38, 51, 182, 210, 216 |
| abstract_inverted_index.± | 294, 298, 302, 306, 311 |
| abstract_inverted_index.31% | 268 |
| abstract_inverted_index.55% | 266 |
| abstract_inverted_index.DSC | 146, 257, 288 |
| abstract_inverted_index.IOV | 258 |
| abstract_inverted_index.Our | 342 |
| abstract_inverted_index.The | 11, 248 |
| abstract_inverted_index.and | 69, 111, 116, 189, 233, 244, 267, 271, 308, 323, 336, 363, 366 |
| abstract_inverted_index.for | 82, 91, 194, 238, 269, 289 |
| abstract_inverted_index.had | 281 |
| abstract_inverted_index.one | 104 |
| abstract_inverted_index.the | 27, 30, 45, 53, 79, 129, 140, 184, 190, 219, 239, 255, 290, 327 |
| abstract_inverted_index.was | 50, 121, 147, 265 |
| abstract_inverted_index.yet | 37 |
| abstract_inverted_index.— | 207, 213 |
| abstract_inverted_index.110, | 230 |
| abstract_inverted_index.112, | 232 |
| abstract_inverted_index.452, | 231 |
| abstract_inverted_index.574, | 229 |
| abstract_inverted_index.Dice | 141 |
| abstract_inverted_index.GYN, | 243 |
| abstract_inverted_index.OARs | 270 |
| abstract_inverted_index.case | 106 |
| abstract_inverted_index.each | 195 |
| abstract_inverted_index.five | 98 |
| abstract_inverted_index.from | 19, 78, 97 |
| abstract_inverted_index.gold | 136 |
| abstract_inverted_index.have | 36 |
| abstract_inverted_index.head | 110 |
| abstract_inverted_index.into | 156 |
| abstract_inverted_index.mean | 293 |
| abstract_inverted_index.more | 361 |
| abstract_inverted_index.most | 330 |
| abstract_inverted_index.neck | 112 |
| abstract_inverted_index.risk | 67 |
| abstract_inverted_index.role | 54 |
| abstract_inverted_index.site | 197 |
| abstract_inverted_index.that | 253 |
| abstract_inverted_index.this | 48, 92 |
| abstract_inverted_index.type | 264 |
| abstract_inverted_index.used | 181 |
| abstract_inverted_index.were | 89, 95, 154, 180, 214, 315 |
| abstract_inverted_index.when | 260 |
| abstract_inverted_index.wide | 337 |
| abstract_inverted_index.with | 132, 200, 329 |
| abstract_inverted_index.zero | 206 |
| abstract_inverted_index.(GI). | 118 |
| abstract_inverted_index.(IOV) | 167 |
| abstract_inverted_index.(OAR) | 68 |
| abstract_inverted_index.0.98) | 312 |
| abstract_inverted_index.After | 223 |
| abstract_inverted_index.Carlo | 177 |
| abstract_inverted_index.Monte | 176 |
| abstract_inverted_index.Organ | 65 |
| abstract_inverted_index.There | 314 |
| abstract_inverted_index.based | 159 |
| abstract_inverted_index.basis | 126 |
| abstract_inverted_index.chain | 175 |
| abstract_inverted_index.clear | 317 |
| abstract_inverted_index.data, | 16 |
| abstract_inverted_index.each: | 107 |
| abstract_inverted_index.fully | 40 |
| abstract_inverted_index.image | 3 |
| abstract_inverted_index.large | 333 |
| abstract_inverted_index.sites | 101 |
| abstract_inverted_index.study | 49, 343 |
| abstract_inverted_index.these | 33 |
| abstract_inverted_index.tumor | 70, 272, 279 |
| abstract_inverted_index.using | 139, 173 |
| abstract_inverted_index.(DSC); | 144 |
| abstract_inverted_index.(GYN), | 115 |
| abstract_inverted_index.0.20), | 299 |
| abstract_inverted_index.0.24), | 307 |
| abstract_inverted_index.0.54), | 303 |
| abstract_inverted_index.Future | 354 |
| abstract_inverted_index.Markov | 174 |
| abstract_inverted_index.across | 326 |
| abstract_inverted_index.binary | 157 |
| abstract_inverted_index.breast | 291 |
| abstract_inverted_index.cases, | 246, 328 |
| abstract_inverted_index.cases. | 313 |
| abstract_inverted_index.common | 56 |
| abstract_inverted_index.cutoff | 259 |
| abstract_inverted_index.expert | 256 |
| abstract_inverted_index.groups | 158 |
| abstract_inverted_index.impact | 218, 285 |
| abstract_inverted_index.linear | 170 |
| abstract_inverted_index.median | 249 |
| abstract_inverted_index.models | 172 |
| abstract_inverted_index.poised | 6 |
| abstract_inverted_index.public | 87 |
| abstract_inverted_index.should | 356 |
| abstract_inverted_index.study. | 93 |
| abstract_inverted_index.utmost | 24 |
| abstract_inverted_index.volume | 71 |
| abstract_inverted_index.H&N | 304 |
| abstract_inverted_index.METHODS | 64 |
| abstract_inverted_index.Medical | 2 |
| abstract_inverted_index.Metrics | 153 |
| abstract_inverted_index.RESULTS | 222 |
| abstract_inverted_index.between | 186, 320 |
| abstract_inverted_index.breast, | 108, 240 |
| abstract_inverted_index.crossed | 254 |
| abstract_inverted_index.dataset | 88 |
| abstract_inverted_index.density | 203, 339 |
| abstract_inverted_index.derived | 18, 96 |
| abstract_inverted_index.disease | 100, 196 |
| abstract_inverted_index.factors | 28, 350 |
| abstract_inverted_index.highest | 202, 338 |
| abstract_inverted_index.imaging | 364 |
| abstract_inverted_index.loosely | 208 |
| abstract_inverted_index.metric. | 152 |
| abstract_inverted_index.metrics | 368 |
| abstract_inverted_index.outcome | 220 |
| abstract_inverted_index.patient | 105 |
| abstract_inverted_index.purpose | 46 |
| abstract_inverted_index.quality | 12, 31, 120, 193, 322 |
| abstract_inverted_index.sarcoma | 300 |
| abstract_inverted_index.studies | 355 |
| abstract_inverted_index.surface | 145 |
| abstract_inverted_index.–0.97 | 297 |
| abstract_inverted_index.(–1.00 | 305 |
| abstract_inverted_index.(–1.04 | 301 |
| abstract_inverted_index.(–2.95 | 310 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.Bayesian | 178, 275 |
| abstract_inverted_index.H&N, | 242 |
| abstract_inverted_index.However, | 26 |
| abstract_inverted_index.Oncology | 86 |
| abstract_inverted_index.analysis | 277 |
| abstract_inverted_index.category | 280 |
| abstract_inverted_index.cutoffs. | 168 |
| abstract_inverted_index.interval | 204 |
| abstract_inverted_index.measure. | 221 |
| abstract_inverted_index.negative | 284 |
| abstract_inverted_index.observer | 57, 130 |
| abstract_inverted_index.patients | 362 |
| abstract_inverted_index.presumed | 349 |
| abstract_inverted_index.provided | 73 |
| abstract_inverted_index.quality. | 353 |
| abstract_inverted_index.remained | 237 |
| abstract_inverted_index.revealed | 278 |
| abstract_inverted_index.sarcoma, | 109, 241 |
| abstract_inverted_index.separate | 99 |
| abstract_inverted_index.standard | 137, 295, 334 |
| abstract_inverted_index.training | 15 |
| abstract_inverted_index.utilized | 90 |
| abstract_inverted_index.volumes, | 273 |
| abstract_inverted_index.Consensus | 83 |
| abstract_inverted_index.Radiation | 85 |
| abstract_inverted_index.Variables | 199 |
| abstract_inverted_index.analogous | 209 |
| abstract_inverted_index.binarized | 191, 287 |
| abstract_inverted_index.clinician | 20 |
| abstract_inverted_index.comparing | 128 |
| abstract_inverted_index.comprised | 102 |
| abstract_inverted_index.consensus | 135 |
| abstract_inverted_index.determine | 52 |
| abstract_inverted_index.excluding | 205 |
| abstract_inverted_index.filtering | 224 |
| abstract_inverted_index.observers | 77 |
| abstract_inverted_index.primarily | 17, 138 |
| abstract_inverted_index.radiation | 75, 227 |
| abstract_inverted_index.recurring | 318 |
| abstract_inverted_index.secondary | 151 |
| abstract_inverted_index.structure | 235, 263 |
| abstract_inverted_index.variables | 59, 188, 325, 331 |
| abstract_inverted_index.(H&N), | 113 |
| abstract_inverted_index.BACKGROUND | 1 |
| abstract_inverted_index.CONCLUSION | 341 |
| abstract_inverted_index.Contouring | 80 |
| abstract_inverted_index.Similarity | 142 |
| abstract_inverted_index.Therefore, | 44 |
| abstract_inverted_index.additional | 358 |
| abstract_inverted_index.considered | 215 |
| abstract_inverted_index.determined | 122 |
| abstract_inverted_index.deviation: | 296 |
| abstract_inverted_index.deviations | 335 |
| abstract_inverted_index.estimation | 179 |
| abstract_inverted_index.highlights | 344 |
| abstract_inverted_index.intervals. | 340 |
| abstract_inverted_index.observers, | 21 |
| abstract_inverted_index.oncologist | 76 |
| abstract_inverted_index.percentage | 250 |
| abstract_inverted_index.practicing | 226 |
| abstract_inverted_index.previously | 161 |
| abstract_inverted_index.regression | 276 |
| abstract_inverted_index.stratified | 155, 261 |
| abstract_inverted_index.understood | 41 |
| abstract_inverted_index.variables, | 360 |
| abstract_inverted_index.workflows. | 10 |
| abstract_inverted_index.Coefficient | 143 |
| abstract_inverted_index.Generalized | 169 |
| abstract_inverted_index.alternative | 367 |
| abstract_inverted_index.association | 185 |
| abstract_inverted_index.demographic | 58, 187, 324, 359 |
| abstract_inverted_index.established | 162 |
| abstract_inverted_index.frequentist | 211 |
| abstract_inverted_index.gynecologic | 114 |
| abstract_inverted_index.importance. | 25 |
| abstract_inverted_index.influencing | 29, 351 |
| abstract_inverted_index.investigate | 183, 357 |
| abstract_inverted_index.modalities, | 365 |
| abstract_inverted_index.quantified. | 43 |
| abstract_inverted_index.separately. | 198 |
| abstract_inverted_index.substantial | 283, 345 |
| abstract_inverted_index.surrounding | 347 |
| abstract_inverted_index.uncertainty | 346 |
| abstract_inverted_index.variability | 166 |
| abstract_inverted_index.(coefficient | 292 |
| abstract_inverted_index.Segmentation | 119 |
| abstract_inverted_index.investigated | 148 |
| abstract_inverted_index.observations | 236, 252 |
| abstract_inverted_index.oncologists, | 228 |
| abstract_inverted_index.performance. | 63 |
| abstract_inverted_index.quantitative | 61 |
| abstract_inverted_index.radiotherapy | 9 |
| abstract_inverted_index.segmentation | 62, 192, 321, 352, 370 |
| abstract_inverted_index.significance | 212 |
| abstract_inverted_index.Collaborative | 81 |
| abstract_inverted_index.Segmentations | 94 |
| abstract_inverted_index.demonstrating | 332 |
| abstract_inverted_index.interobserver | 165 |
| abstract_inverted_index.mixed-effects | 171 |
| abstract_inverted_index.relationships | 319 |
| abstract_inverted_index.respectively. | 247, 274 |
| abstract_inverted_index.revolutionize | 8 |
| abstract_inverted_index.segmentations | 35, 72, 131 |
| abstract_inverted_index.substantially | 217 |
| abstract_inverted_index.acceptability. | 371 |
| abstract_inverted_index.conventionally | 348 |
| abstract_inverted_index.expert-derived | 134, 164 |
| abstract_inverted_index.gastrointestinal | 117 |
| abstract_inverted_index.auto-segmentation | 4, 14 |
| abstract_inverted_index.clinician-derived | 34 |
| abstract_inverted_index.structure-specific | 163 |
| abstract_inverted_index.structure-by-structure | 125 |
| cited_by_percentile_year | |
| corresponding_author_ids | https://openalex.org/A5056322583, https://openalex.org/A5052234283 |
| countries_distinct_count | 2 |
| institutions_distinct_count | 21 |
| corresponding_institution_ids | https://openalex.org/I1343551460, https://openalex.org/I4210089486 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/3 |
| sustainable_development_goals[0].score | 0.41999998688697815 |
| sustainable_development_goals[0].display_name | Good health and well-being |
| citation_normalized_percentile.value | 0.17207982 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |