Machine Learning Augmented Interpretation of Chest X-rays: A Systematic Review Article Swipe
Hassan K. Ahmad
,
Michael Milne
,
Quinlan D. Buchlak
,
Nalan Ektas
,
Georgina Sanderson
,
Hadi Chamtie
,
Sajith Karunasena
,
Jason Chiang
,
Xavier Holt
,
Cyril Tang
,
Jarrel Seah
,
Georgina Bottrell
,
Nazanin Esmaili
,
Peter Brotchie
,
Catherine M Jones
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/diagnostics13040743
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/diagnostics13040743
Limitations of the chest X-ray (CXR) have resulted in attempts to create machine learning systems to assist clinicians and improve interpretation accuracy. An understanding of the capabilities and limitations of modern machine learning systems is necessary for clinicians as these tools begin to permeate practice. This systematic review aimed to provide an overview of machine learning applications designed to facilitate CXR interpretation. A systematic search strategy was executed to identify research into machine learning algorithms capable of detecting >2 radiographic findings on CXRs published between January 2020 and September 2022. Model details and study characteristics, including risk of bias and quality, were summarized. Initially, 2248 articles were retrieved, with 46 included in the final review. Published models demonstrated strong standalone performance and were typically as accurate, or more accurate, than radiologists or non-radiologist clinicians. Multiple studies demonstrated an improvement in the clinical finding classification performance of clinicians when models acted as a diagnostic assistance device. Device performance was compared with that of clinicians in 30% of studies, while effects on clinical perception and diagnosis were evaluated in 19%. Only one study was prospectively run. On average, 128,662 images were used to train and validate models. Most classified less than eight clinical findings, while the three most comprehensive models classified 54, 72, and 124 findings. This review suggests that machine learning devices designed to facilitate CXR interpretation perform strongly, improve the detection performance of clinicians, and improve the efficiency of radiology workflow. Several limitations were identified, and clinician involvement and expertise will be key to driving the safe implementation of quality CXR machine learning systems.
Related Topics
Concepts
Metadata
- Type
- review
- Language
- en
- Landing Page
- https://doi.org/10.3390/diagnostics13040743
- https://www.mdpi.com/2075-4418/13/4/743/pdf?version=1677050594
- OA Status
- gold
- Cited By
- 29
- References
- 122
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4321095938
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4321095938Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/diagnostics13040743Digital Object Identifier
- Title
-
Machine Learning Augmented Interpretation of Chest X-rays: A Systematic ReviewWork title
- Type
-
reviewOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-02-15Full publication date if available
- Authors
-
Hassan K. Ahmad, Michael Milne, Quinlan D. Buchlak, Nalan Ektas, Georgina Sanderson, Hadi Chamtie, Sajith Karunasena, Jason Chiang, Xavier Holt, Cyril Tang, Jarrel Seah, Georgina Bottrell, Nazanin Esmaili, Peter Brotchie, Catherine M JonesList of authors in order
- Landing page
-
https://doi.org/10.3390/diagnostics13040743Publisher landing page
- PDF URL
-
https://www.mdpi.com/2075-4418/13/4/743/pdf?version=1677050594Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/2075-4418/13/4/743/pdf?version=1677050594Direct OA link when available
- Concepts
-
Interpretation (philosophy), Medical physics, Computer science, Artificial intelligence, Natural language processing, Medicine, Programming languageTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
29Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 12, 2024: 9, 2023: 8Per-year citation counts (last 5 years)
- References (count)
-
122Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4321095938 |
|---|---|
| doi | https://doi.org/10.3390/diagnostics13040743 |
| ids.doi | https://doi.org/10.3390/diagnostics13040743 |
| ids.pmid | https://pubmed.ncbi.nlm.nih.gov/36832231 |
| ids.openalex | https://openalex.org/W4321095938 |
| fwci | 8.96259399 |
| type | review |
| title | Machine Learning Augmented Interpretation of Chest X-rays: A Systematic Review |
| biblio.issue | 4 |
| biblio.volume | 13 |
| biblio.last_page | 743 |
| biblio.first_page | 743 |
| topics[0].id | https://openalex.org/T11894 |
| topics[0].field.id | https://openalex.org/fields/27 |
| topics[0].field.display_name | Medicine |
| topics[0].score | 0.9987999796867371 |
| topics[0].domain.id | https://openalex.org/domains/4 |
| topics[0].domain.display_name | Health Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/2741 |
| topics[0].subfield.display_name | Radiology, Nuclear Medicine and Imaging |
| topics[0].display_name | Radiology practices and education |
| topics[1].id | https://openalex.org/T11775 |
| topics[1].field.id | https://openalex.org/fields/27 |
| topics[1].field.display_name | Medicine |
| topics[1].score | 0.9983000159263611 |
| 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 | COVID-19 diagnosis using AI |
| topics[2].id | https://openalex.org/T12422 |
| topics[2].field.id | https://openalex.org/fields/27 |
| topics[2].field.display_name | Medicine |
| topics[2].score | 0.9979000091552734 |
| 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 | Radiomics and Machine Learning in Medical Imaging |
| is_xpac | False |
| apc_list.value | 2000 |
| apc_list.currency | CHF |
| apc_list.value_usd | 2165 |
| apc_paid.value | 2000 |
| apc_paid.currency | CHF |
| apc_paid.value_usd | 2165 |
| concepts[0].id | https://openalex.org/C527412718 |
| concepts[0].level | 2 |
| concepts[0].score | 0.687663197517395 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q855395 |
| concepts[0].display_name | Interpretation (philosophy) |
| concepts[1].id | https://openalex.org/C19527891 |
| concepts[1].level | 1 |
| concepts[1].score | 0.434389591217041 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q1120908 |
| concepts[1].display_name | Medical physics |
| concepts[2].id | https://openalex.org/C41008148 |
| concepts[2].level | 0 |
| concepts[2].score | 0.40822792053222656 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[2].display_name | Computer science |
| concepts[3].id | https://openalex.org/C154945302 |
| concepts[3].level | 1 |
| concepts[3].score | 0.3426538109779358 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[3].display_name | Artificial intelligence |
| concepts[4].id | https://openalex.org/C204321447 |
| concepts[4].level | 1 |
| concepts[4].score | 0.32002031803131104 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q30642 |
| concepts[4].display_name | Natural language processing |
| concepts[5].id | https://openalex.org/C71924100 |
| concepts[5].level | 0 |
| concepts[5].score | 0.2893756628036499 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q11190 |
| concepts[5].display_name | Medicine |
| concepts[6].id | https://openalex.org/C199360897 |
| concepts[6].level | 1 |
| concepts[6].score | 0.10741963982582092 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q9143 |
| concepts[6].display_name | Programming language |
| keywords[0].id | https://openalex.org/keywords/interpretation |
| keywords[0].score | 0.687663197517395 |
| keywords[0].display_name | Interpretation (philosophy) |
| keywords[1].id | https://openalex.org/keywords/medical-physics |
| keywords[1].score | 0.434389591217041 |
| keywords[1].display_name | Medical physics |
| keywords[2].id | https://openalex.org/keywords/computer-science |
| keywords[2].score | 0.40822792053222656 |
| keywords[2].display_name | Computer science |
| keywords[3].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[3].score | 0.3426538109779358 |
| keywords[3].display_name | Artificial intelligence |
| keywords[4].id | https://openalex.org/keywords/natural-language-processing |
| keywords[4].score | 0.32002031803131104 |
| keywords[4].display_name | Natural language processing |
| keywords[5].id | https://openalex.org/keywords/medicine |
| keywords[5].score | 0.2893756628036499 |
| keywords[5].display_name | Medicine |
| keywords[6].id | https://openalex.org/keywords/programming-language |
| keywords[6].score | 0.10741963982582092 |
| keywords[6].display_name | Programming language |
| language | en |
| locations[0].id | doi:10.3390/diagnostics13040743 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S4210172076 |
| locations[0].source.issn | 2075-4418 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 2075-4418 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | True |
| locations[0].source.display_name | Diagnostics |
| locations[0].source.host_organization | https://openalex.org/P4310310987 |
| locations[0].source.host_organization_name | Multidisciplinary Digital Publishing Institute |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310310987 |
| locations[0].source.host_organization_lineage_names | Multidisciplinary Digital Publishing Institute |
| locations[0].license | cc-by |
| locations[0].pdf_url | https://www.mdpi.com/2075-4418/13/4/743/pdf?version=1677050594 |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | https://openalex.org/licenses/cc-by |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | Diagnostics |
| locations[0].landing_page_url | https://doi.org/10.3390/diagnostics13040743 |
| locations[1].id | pmid:36832231 |
| 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 | Diagnostics (Basel, Switzerland) |
| locations[1].landing_page_url | https://pubmed.ncbi.nlm.nih.gov/36832231 |
| locations[2].id | pmh:oai:doaj.org/article:571a11ab740e4109a505dc682f9f2a14 |
| locations[2].is_oa | False |
| locations[2].source.id | https://openalex.org/S4306401280 |
| 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 | DOAJ (DOAJ: Directory of Open Access Journals) |
| locations[2].source.host_organization | |
| locations[2].source.host_organization_name | |
| locations[2].license | |
| locations[2].pdf_url | |
| locations[2].version | submittedVersion |
| locations[2].raw_type | article |
| locations[2].license_id | |
| locations[2].is_accepted | False |
| locations[2].is_published | False |
| locations[2].raw_source_name | Diagnostics, Vol 13, Iss 4, p 743 (2023) |
| locations[2].landing_page_url | https://doaj.org/article/571a11ab740e4109a505dc682f9f2a14 |
| locations[3].id | pmh:oai:mdpi.com:/2075-4418/13/4/743/ |
| locations[3].is_oa | True |
| locations[3].source.id | https://openalex.org/S4306400947 |
| locations[3].source.issn | |
| locations[3].source.type | repository |
| locations[3].source.is_oa | True |
| locations[3].source.issn_l | |
| locations[3].source.is_core | False |
| locations[3].source.is_in_doaj | False |
| locations[3].source.display_name | MDPI (MDPI AG) |
| locations[3].source.host_organization | https://openalex.org/I4210097602 |
| locations[3].source.host_organization_name | Multidisciplinary Digital Publishing Institute (Switzerland) |
| locations[3].source.host_organization_lineage | https://openalex.org/I4210097602 |
| locations[3].license | cc-by |
| locations[3].pdf_url | |
| locations[3].version | submittedVersion |
| locations[3].raw_type | Text |
| locations[3].license_id | https://openalex.org/licenses/cc-by |
| locations[3].is_accepted | False |
| locations[3].is_published | False |
| locations[3].raw_source_name | Diagnostics |
| locations[3].landing_page_url | https://dx.doi.org/10.3390/diagnostics13040743 |
| locations[4].id | pmh:oai:pubmedcentral.nih.gov:9955112 |
| locations[4].is_oa | True |
| locations[4].source.id | https://openalex.org/S2764455111 |
| locations[4].source.issn | |
| locations[4].source.type | repository |
| locations[4].source.is_oa | False |
| locations[4].source.issn_l | |
| locations[4].source.is_core | False |
| locations[4].source.is_in_doaj | False |
| locations[4].source.display_name | PubMed Central |
| locations[4].source.host_organization | https://openalex.org/I1299303238 |
| locations[4].source.host_organization_name | National Institutes of Health |
| locations[4].source.host_organization_lineage | https://openalex.org/I1299303238 |
| locations[4].license | other-oa |
| locations[4].pdf_url | |
| locations[4].version | submittedVersion |
| locations[4].raw_type | Text |
| locations[4].license_id | https://openalex.org/licenses/other-oa |
| locations[4].is_accepted | False |
| locations[4].is_published | False |
| locations[4].raw_source_name | Diagnostics (Basel) |
| locations[4].landing_page_url | https://www.ncbi.nlm.nih.gov/pmc/articles/9955112 |
| indexed_in | crossref, doaj, pubmed |
| authorships[0].author.id | https://openalex.org/A5090336817 |
| authorships[0].author.orcid | |
| authorships[0].author.display_name | Hassan K. Ahmad |
| authorships[0].countries | AU |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I2800079252 |
| authorships[0].affiliations[0].raw_affiliation_string | Department of Emergency Medicine, Royal North Shore Hospital, Sydney, NSW 2065, Australia |
| authorships[0].affiliations[1].raw_affiliation_string | Annalise.ai, Sydney, NSW 2000, Australia |
| authorships[0].institutions[0].id | https://openalex.org/I2800079252 |
| authorships[0].institutions[0].ror | https://ror.org/02gs2e959 |
| authorships[0].institutions[0].type | healthcare |
| authorships[0].institutions[0].lineage | https://openalex.org/I2800079252 |
| authorships[0].institutions[0].country_code | AU |
| authorships[0].institutions[0].display_name | Royal North Shore Hospital |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Hassan K. Ahmad |
| authorships[0].is_corresponding | True |
| authorships[0].raw_affiliation_strings | Annalise.ai, Sydney, NSW 2000, Australia, Department of Emergency Medicine, Royal North Shore Hospital, Sydney, NSW 2065, Australia |
| authorships[1].author.id | https://openalex.org/A5024489761 |
| authorships[1].author.orcid | https://orcid.org/0000-0003-2082-5723 |
| authorships[1].author.display_name | Michael Milne |
| authorships[1].affiliations[0].raw_affiliation_string | Annalise.ai, Sydney, NSW 2000, Australia |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Michael R. Milne |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | Annalise.ai, Sydney, NSW 2000, Australia |
| authorships[2].author.id | https://openalex.org/A5014188815 |
| authorships[2].author.orcid | https://orcid.org/0000-0001-6749-3223 |
| authorships[2].author.display_name | Quinlan D. Buchlak |
| authorships[2].countries | AU |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I4210121067 |
| authorships[2].affiliations[0].raw_affiliation_string | Department of Neurosurgery, Monash Health, Melbourne, VIC 3168, Australia |
| authorships[2].affiliations[1].raw_affiliation_string | Annalise.ai, Sydney, NSW 2000, Australia |
| authorships[2].affiliations[2].institution_ids | https://openalex.org/I93396115 |
| authorships[2].affiliations[2].raw_affiliation_string | School of Medicine, University of Notre Dame Australia, Sydney, NSW 2007, Australia |
| authorships[2].institutions[0].id | https://openalex.org/I4210121067 |
| authorships[2].institutions[0].ror | https://ror.org/02t1bej08 |
| authorships[2].institutions[0].type | healthcare |
| authorships[2].institutions[0].lineage | https://openalex.org/I4210121067 |
| authorships[2].institutions[0].country_code | AU |
| authorships[2].institutions[0].display_name | Monash Health |
| authorships[2].institutions[1].id | https://openalex.org/I93396115 |
| authorships[2].institutions[1].ror | https://ror.org/02stey378 |
| authorships[2].institutions[1].type | education |
| authorships[2].institutions[1].lineage | https://openalex.org/I93396115 |
| authorships[2].institutions[1].country_code | AU |
| authorships[2].institutions[1].display_name | The University of Notre Dame Australia |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Quinlan D. Buchlak |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | Annalise.ai, Sydney, NSW 2000, Australia, Department of Neurosurgery, Monash Health, Melbourne, VIC 3168, Australia, School of Medicine, University of Notre Dame Australia, Sydney, NSW 2007, Australia |
| authorships[3].author.id | https://openalex.org/A5030406118 |
| authorships[3].author.orcid | |
| authorships[3].author.display_name | Nalan Ektas |
| authorships[3].affiliations[0].raw_affiliation_string | Annalise.ai, Sydney, NSW 2000, Australia |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Nalan Ektas |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | Annalise.ai, Sydney, NSW 2000, Australia |
| authorships[4].author.id | https://openalex.org/A5083746910 |
| authorships[4].author.orcid | |
| authorships[4].author.display_name | Georgina Sanderson |
| authorships[4].affiliations[0].raw_affiliation_string | Annalise.ai, Sydney, NSW 2000, Australia |
| authorships[4].author_position | middle |
| authorships[4].raw_author_name | Georgina Sanderson |
| authorships[4].is_corresponding | False |
| authorships[4].raw_affiliation_strings | Annalise.ai, Sydney, NSW 2000, Australia |
| authorships[5].author.id | https://openalex.org/A5002301288 |
| authorships[5].author.orcid | |
| authorships[5].author.display_name | Hadi Chamtie |
| authorships[5].affiliations[0].raw_affiliation_string | Annalise.ai, Sydney, NSW 2000, Australia |
| authorships[5].author_position | middle |
| authorships[5].raw_author_name | Hadi Chamtie |
| authorships[5].is_corresponding | False |
| authorships[5].raw_affiliation_strings | Annalise.ai, Sydney, NSW 2000, Australia |
| authorships[6].author.id | https://openalex.org/A5015370877 |
| authorships[6].author.orcid | |
| authorships[6].author.display_name | Sajith Karunasena |
| authorships[6].affiliations[0].raw_affiliation_string | Annalise.ai, Sydney, NSW 2000, Australia |
| authorships[6].author_position | middle |
| authorships[6].raw_author_name | Sajith Karunasena |
| authorships[6].is_corresponding | False |
| authorships[6].raw_affiliation_strings | Annalise.ai, Sydney, NSW 2000, Australia |
| authorships[7].author.id | https://openalex.org/A5078908746 |
| authorships[7].author.orcid | https://orcid.org/0000-0002-4370-8063 |
| authorships[7].author.display_name | Jason Chiang |
| authorships[7].countries | AU |
| authorships[7].affiliations[0].institution_ids | https://openalex.org/I129604602 |
| authorships[7].affiliations[0].raw_affiliation_string | Westmead Applied Research Centre, University of Sydney, Sydney, NSW 2006, Australia |
| authorships[7].affiliations[1].institution_ids | https://openalex.org/I165779595 |
| authorships[7].affiliations[1].raw_affiliation_string | Department of General Practice, University of Melbourne, Melbourne, VIC 3010, Australia |
| authorships[7].affiliations[2].raw_affiliation_string | Annalise.ai, Sydney, NSW 2000, Australia |
| authorships[7].institutions[0].id | https://openalex.org/I165779595 |
| authorships[7].institutions[0].ror | https://ror.org/01ej9dk98 |
| authorships[7].institutions[0].type | education |
| authorships[7].institutions[0].lineage | https://openalex.org/I165779595 |
| authorships[7].institutions[0].country_code | AU |
| authorships[7].institutions[0].display_name | The University of Melbourne |
| authorships[7].institutions[1].id | https://openalex.org/I129604602 |
| authorships[7].institutions[1].ror | https://ror.org/0384j8v12 |
| authorships[7].institutions[1].type | education |
| authorships[7].institutions[1].lineage | https://openalex.org/I129604602 |
| authorships[7].institutions[1].country_code | AU |
| authorships[7].institutions[1].display_name | The University of Sydney |
| authorships[7].author_position | middle |
| authorships[7].raw_author_name | Jason Chiang |
| authorships[7].is_corresponding | False |
| authorships[7].raw_affiliation_strings | Annalise.ai, Sydney, NSW 2000, Australia, Department of General Practice, University of Melbourne, Melbourne, VIC 3010, Australia, Westmead Applied Research Centre, University of Sydney, Sydney, NSW 2006, Australia |
| authorships[8].author.id | https://openalex.org/A5088703337 |
| authorships[8].author.orcid | |
| authorships[8].author.display_name | Xavier Holt |
| authorships[8].affiliations[0].raw_affiliation_string | Annalise.ai, Sydney, NSW 2000, Australia |
| authorships[8].author_position | middle |
| authorships[8].raw_author_name | Xavier Holt |
| authorships[8].is_corresponding | False |
| authorships[8].raw_affiliation_strings | Annalise.ai, Sydney, NSW 2000, Australia |
| authorships[9].author.id | https://openalex.org/A5091679899 |
| authorships[9].author.orcid | https://orcid.org/0000-0002-1844-0050 |
| authorships[9].author.display_name | Cyril Tang |
| authorships[9].affiliations[0].raw_affiliation_string | Annalise.ai, Sydney, NSW 2000, Australia |
| authorships[9].author_position | middle |
| authorships[9].raw_author_name | Cyril H. M. Tang |
| authorships[9].is_corresponding | False |
| authorships[9].raw_affiliation_strings | Annalise.ai, Sydney, NSW 2000, Australia |
| authorships[10].author.id | https://openalex.org/A5043340777 |
| authorships[10].author.orcid | https://orcid.org/0000-0002-2305-7873 |
| authorships[10].author.display_name | Jarrel Seah |
| authorships[10].countries | AU |
| authorships[10].affiliations[0].raw_affiliation_string | Annalise.ai, Sydney, NSW 2000, Australia |
| authorships[10].affiliations[1].institution_ids | https://openalex.org/I4210163178 |
| authorships[10].affiliations[1].raw_affiliation_string | Department of Radiology, Alfred Health, Melbourne, VIC 3004, Australia |
| authorships[10].institutions[0].id | https://openalex.org/I4210163178 |
| authorships[10].institutions[0].ror | https://ror.org/04scfb908 |
| authorships[10].institutions[0].type | healthcare |
| authorships[10].institutions[0].lineage | https://openalex.org/I4210163178 |
| authorships[10].institutions[0].country_code | AU |
| authorships[10].institutions[0].display_name | Alfred Health |
| authorships[10].author_position | middle |
| authorships[10].raw_author_name | Jarrel C. Y. Seah |
| authorships[10].is_corresponding | False |
| authorships[10].raw_affiliation_strings | Annalise.ai, Sydney, NSW 2000, Australia, Department of Radiology, Alfred Health, Melbourne, VIC 3004, Australia |
| authorships[11].author.id | https://openalex.org/A5016629546 |
| authorships[11].author.orcid | |
| authorships[11].author.display_name | Georgina Bottrell |
| authorships[11].affiliations[0].raw_affiliation_string | Annalise.ai, Sydney, NSW 2000, Australia |
| authorships[11].author_position | middle |
| authorships[11].raw_author_name | Georgina Bottrell |
| authorships[11].is_corresponding | False |
| authorships[11].raw_affiliation_strings | Annalise.ai, Sydney, NSW 2000, Australia |
| authorships[12].author.id | https://openalex.org/A5086177281 |
| authorships[12].author.orcid | https://orcid.org/0000-0002-0605-4996 |
| authorships[12].author.display_name | Nazanin Esmaili |
| authorships[12].countries | AU |
| authorships[12].affiliations[0].institution_ids | https://openalex.org/I114017466 |
| authorships[12].affiliations[0].raw_affiliation_string | Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, NSW 2007, Australia |
| authorships[12].affiliations[1].institution_ids | https://openalex.org/I93396115 |
| authorships[12].affiliations[1].raw_affiliation_string | School of Medicine, University of Notre Dame Australia, Sydney, NSW 2007, Australia |
| authorships[12].institutions[0].id | https://openalex.org/I93396115 |
| authorships[12].institutions[0].ror | https://ror.org/02stey378 |
| authorships[12].institutions[0].type | education |
| authorships[12].institutions[0].lineage | https://openalex.org/I93396115 |
| authorships[12].institutions[0].country_code | AU |
| authorships[12].institutions[0].display_name | The University of Notre Dame Australia |
| authorships[12].institutions[1].id | https://openalex.org/I114017466 |
| authorships[12].institutions[1].ror | https://ror.org/03f0f6041 |
| authorships[12].institutions[1].type | education |
| authorships[12].institutions[1].lineage | https://openalex.org/I114017466 |
| authorships[12].institutions[1].country_code | AU |
| authorships[12].institutions[1].display_name | University of Technology Sydney |
| authorships[12].author_position | middle |
| authorships[12].raw_author_name | Nazanin Esmaili |
| authorships[12].is_corresponding | False |
| authorships[12].raw_affiliation_strings | Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, NSW 2007, Australia, School of Medicine, University of Notre Dame Australia, Sydney, NSW 2007, Australia |
| authorships[13].author.id | https://openalex.org/A5064195985 |
| authorships[13].author.orcid | https://orcid.org/0000-0003-2313-9067 |
| authorships[13].author.display_name | Peter Brotchie |
| authorships[13].countries | AU |
| authorships[13].affiliations[0].institution_ids | https://openalex.org/I4210098850 |
| authorships[13].affiliations[0].raw_affiliation_string | Department of Radiology, St Vincent's Health Australia, Melbourne, VIC 3065, Australia |
| authorships[13].affiliations[1].raw_affiliation_string | Annalise.ai, Sydney, NSW 2000, Australia |
| authorships[13].institutions[0].id | https://openalex.org/I4210098850 |
| authorships[13].institutions[0].ror | https://ror.org/012nkbb42 |
| authorships[13].institutions[0].type | healthcare |
| authorships[13].institutions[0].lineage | https://openalex.org/I4210098850 |
| authorships[13].institutions[0].country_code | AU |
| authorships[13].institutions[0].display_name | St Vincent's Health |
| authorships[13].author_position | middle |
| authorships[13].raw_author_name | Peter Brotchie |
| authorships[13].is_corresponding | False |
| authorships[13].raw_affiliation_strings | Annalise.ai, Sydney, NSW 2000, Australia, Department of Radiology, St Vincent's Health Australia, Melbourne, VIC 3065, Australia |
| authorships[14].author.id | https://openalex.org/A5101815694 |
| authorships[14].author.orcid | https://orcid.org/0000-0003-2399-8929 |
| authorships[14].author.display_name | Catherine M Jones |
| authorships[14].countries | AU |
| authorships[14].affiliations[0].raw_affiliation_string | Annalise.ai, Sydney, NSW 2000, Australia |
| authorships[14].affiliations[1].institution_ids | https://openalex.org/I56590836 |
| authorships[14].affiliations[1].raw_affiliation_string | School of Public and Preventive Health, Monash University, Clayton, VIC 3800, Australia |
| authorships[14].affiliations[2].raw_affiliation_string | I-MED Radiology Network, Brisbane, QLD 4006, Australia |
| authorships[14].affiliations[3].institution_ids | https://openalex.org/I129604602 |
| authorships[14].affiliations[3].raw_affiliation_string | Department of Clinical Imaging Science, University of Sydney, Sydney, NSW 2006, Australia |
| authorships[14].institutions[0].id | https://openalex.org/I56590836 |
| authorships[14].institutions[0].ror | https://ror.org/02bfwt286 |
| authorships[14].institutions[0].type | education |
| authorships[14].institutions[0].lineage | https://openalex.org/I56590836 |
| authorships[14].institutions[0].country_code | AU |
| authorships[14].institutions[0].display_name | Monash University |
| authorships[14].institutions[1].id | https://openalex.org/I129604602 |
| authorships[14].institutions[1].ror | https://ror.org/0384j8v12 |
| authorships[14].institutions[1].type | education |
| authorships[14].institutions[1].lineage | https://openalex.org/I129604602 |
| authorships[14].institutions[1].country_code | AU |
| authorships[14].institutions[1].display_name | The University of Sydney |
| authorships[14].author_position | last |
| authorships[14].raw_author_name | Catherine Jones |
| authorships[14].is_corresponding | False |
| authorships[14].raw_affiliation_strings | Annalise.ai, Sydney, NSW 2000, Australia, Department of Clinical Imaging Science, University of Sydney, Sydney, NSW 2006, Australia, I-MED Radiology Network, Brisbane, QLD 4006, Australia, School of Public and Preventive Health, Monash University, Clayton, VIC 3800, Australia |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://www.mdpi.com/2075-4418/13/4/743/pdf?version=1677050594 |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Machine Learning Augmented Interpretation of Chest X-rays: A Systematic Review |
| has_fulltext | True |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T11894 |
| primary_topic.field.id | https://openalex.org/fields/27 |
| primary_topic.field.display_name | Medicine |
| primary_topic.score | 0.9987999796867371 |
| primary_topic.domain.id | https://openalex.org/domains/4 |
| primary_topic.domain.display_name | Health Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/2741 |
| primary_topic.subfield.display_name | Radiology, Nuclear Medicine and Imaging |
| primary_topic.display_name | Radiology practices and education |
| related_works | https://openalex.org/W2748952813, https://openalex.org/W3183204001, https://openalex.org/W4327743144, https://openalex.org/W4388567440, https://openalex.org/W4386782890, https://openalex.org/W4313320911, https://openalex.org/W2390279801, https://openalex.org/W2607424049, https://openalex.org/W4245077728, https://openalex.org/W3204019825 |
| cited_by_count | 29 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 12 |
| counts_by_year[1].year | 2024 |
| counts_by_year[1].cited_by_count | 9 |
| counts_by_year[2].year | 2023 |
| counts_by_year[2].cited_by_count | 8 |
| locations_count | 5 |
| best_oa_location.id | doi:10.3390/diagnostics13040743 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S4210172076 |
| best_oa_location.source.issn | 2075-4418 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 2075-4418 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | True |
| best_oa_location.source.display_name | Diagnostics |
| best_oa_location.source.host_organization | https://openalex.org/P4310310987 |
| best_oa_location.source.host_organization_name | Multidisciplinary Digital Publishing Institute |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310310987 |
| best_oa_location.source.host_organization_lineage_names | Multidisciplinary Digital Publishing Institute |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | https://www.mdpi.com/2075-4418/13/4/743/pdf?version=1677050594 |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | Diagnostics |
| best_oa_location.landing_page_url | https://doi.org/10.3390/diagnostics13040743 |
| primary_location.id | doi:10.3390/diagnostics13040743 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S4210172076 |
| primary_location.source.issn | 2075-4418 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 2075-4418 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | True |
| primary_location.source.display_name | Diagnostics |
| primary_location.source.host_organization | https://openalex.org/P4310310987 |
| primary_location.source.host_organization_name | Multidisciplinary Digital Publishing Institute |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310310987 |
| primary_location.source.host_organization_lineage_names | Multidisciplinary Digital Publishing Institute |
| primary_location.license | cc-by |
| primary_location.pdf_url | https://www.mdpi.com/2075-4418/13/4/743/pdf?version=1677050594 |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | https://openalex.org/licenses/cc-by |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | Diagnostics |
| primary_location.landing_page_url | https://doi.org/10.3390/diagnostics13040743 |
| publication_date | 2023-02-15 |
| publication_year | 2023 |
| referenced_works | https://openalex.org/W2022683896, https://openalex.org/W2126629875, https://openalex.org/W2587787457, https://openalex.org/W2559874490, https://openalex.org/W2412795592, https://openalex.org/W2099031764, https://openalex.org/W2119521461, https://openalex.org/W3173979594, https://openalex.org/W3092018978, https://openalex.org/W2966977115, https://openalex.org/W3163243254, https://openalex.org/W2998024276, https://openalex.org/W2952971376, https://openalex.org/W4220875899, https://openalex.org/W3011945319, https://openalex.org/W3036941862, https://openalex.org/W3198421214, https://openalex.org/W4220807233, https://openalex.org/W3110685181, https://openalex.org/W3157153031, https://openalex.org/W4220800546, https://openalex.org/W4285101292, https://openalex.org/W3032290212, https://openalex.org/W2980965120, https://openalex.org/W3045458843, https://openalex.org/W2944591725, https://openalex.org/W2895598278, https://openalex.org/W2894319790, https://openalex.org/W2559794190, https://openalex.org/W3036298167, https://openalex.org/W2982580298, https://openalex.org/W2977601947, https://openalex.org/W3171849353, https://openalex.org/W4238117743, https://openalex.org/W2007872832, https://openalex.org/W2907554860, https://openalex.org/W3123893780, https://openalex.org/W4200486940, https://openalex.org/W3157027387, https://openalex.org/W4293802305, https://openalex.org/W3126581477, https://openalex.org/W3139487216, https://openalex.org/W3159381686, https://openalex.org/W2611650229, https://openalex.org/W3103027491, https://openalex.org/W3038187447, https://openalex.org/W6776676601, https://openalex.org/W6757575617, https://openalex.org/W3083277824, https://openalex.org/W2063878321, https://openalex.org/W3092752870, https://openalex.org/W3188837168, https://openalex.org/W3156761880, https://openalex.org/W3168070634, https://openalex.org/W4220936641, https://openalex.org/W3157655146, https://openalex.org/W6798017362, https://openalex.org/W4213157282, https://openalex.org/W4213439844, https://openalex.org/W6794118553, https://openalex.org/W2396881363, https://openalex.org/W4205355705, https://openalex.org/W3186114585, https://openalex.org/W4214483752, https://openalex.org/W3131052227, https://openalex.org/W4291901522, https://openalex.org/W3093220356, https://openalex.org/W2991676991, https://openalex.org/W3159817553, https://openalex.org/W3107467375, https://openalex.org/W2912664121, https://openalex.org/W3148118841, https://openalex.org/W2989639981, https://openalex.org/W3100236889, https://openalex.org/W2152772232, https://openalex.org/W3122459568, https://openalex.org/W3187152264, https://openalex.org/W4288751772, https://openalex.org/W3177044444, https://openalex.org/W3207052288, https://openalex.org/W4226120516, https://openalex.org/W3091770411, https://openalex.org/W6639867372, https://openalex.org/W3137280709, https://openalex.org/W4297200255, https://openalex.org/W3033271857, https://openalex.org/W3214202315, https://openalex.org/W2956897601, https://openalex.org/W3015489699, https://openalex.org/W3092743670, https://openalex.org/W3162228145, https://openalex.org/W3161534082, https://openalex.org/W2964081807, https://openalex.org/W2963446712, https://openalex.org/W2194775991, https://openalex.org/W2986571455, https://openalex.org/W2281090488, https://openalex.org/W6772878348, https://openalex.org/W3112990870, https://openalex.org/W2098995101, https://openalex.org/W2965300902, https://openalex.org/W1874293710, https://openalex.org/W2995225687, https://openalex.org/W2087564945, https://openalex.org/W2913081511, https://openalex.org/W3041357272, https://openalex.org/W2906295032, https://openalex.org/W3032075591, https://openalex.org/W2793678581, https://openalex.org/W3204611206, https://openalex.org/W3153585807, https://openalex.org/W3199318857, https://openalex.org/W3101156210, https://openalex.org/W3081902266, https://openalex.org/W3040676006, https://openalex.org/W3177694721, https://openalex.org/W3004422652, https://openalex.org/W2963466845, https://openalex.org/W4206966452, https://openalex.org/W1904878066, https://openalex.org/W3130265027, https://openalex.org/W4226108947 |
| referenced_works_count | 122 |
| abstract_inverted_index.A | 62 |
| abstract_inverted_index.a | 151 |
| abstract_inverted_index.46 | 109 |
| abstract_inverted_index.An | 22 |
| abstract_inverted_index.On | 184 |
| abstract_inverted_index.an | 51, 137 |
| abstract_inverted_index.as | 38, 124, 150 |
| abstract_inverted_index.be | 251 |
| abstract_inverted_index.in | 8, 111, 139, 163, 176 |
| abstract_inverted_index.is | 34 |
| abstract_inverted_index.of | 1, 24, 29, 53, 76, 97, 145, 161, 165, 232, 238, 258 |
| abstract_inverted_index.on | 81, 169 |
| abstract_inverted_index.or | 126, 131 |
| abstract_inverted_index.to | 10, 15, 42, 49, 58, 68, 190, 222, 253 |
| abstract_inverted_index.124 | 212 |
| abstract_inverted_index.30% | 164 |
| abstract_inverted_index.54, | 209 |
| abstract_inverted_index.72, | 210 |
| abstract_inverted_index.CXR | 60, 224, 260 |
| abstract_inverted_index.and | 18, 27, 87, 92, 99, 121, 172, 192, 211, 234, 245, 248 |
| abstract_inverted_index.for | 36 |
| abstract_inverted_index.key | 252 |
| abstract_inverted_index.one | 179 |
| abstract_inverted_index.the | 2, 25, 112, 140, 203, 229, 236, 255 |
| abstract_inverted_index.was | 66, 157, 181 |
| abstract_inverted_index.19%. | 177 |
| abstract_inverted_index.2020 | 86 |
| abstract_inverted_index.2248 | 104 |
| abstract_inverted_index.CXRs | 82 |
| abstract_inverted_index.Most | 195 |
| abstract_inverted_index.Only | 178 |
| abstract_inverted_index.This | 45, 214 |
| abstract_inverted_index.bias | 98 |
| abstract_inverted_index.have | 6 |
| abstract_inverted_index.into | 71 |
| abstract_inverted_index.less | 197 |
| abstract_inverted_index.more | 127 |
| abstract_inverted_index.most | 205 |
| abstract_inverted_index.risk | 96 |
| abstract_inverted_index.run. | 183 |
| abstract_inverted_index.safe | 256 |
| abstract_inverted_index.than | 129, 198 |
| abstract_inverted_index.that | 160, 217 |
| abstract_inverted_index.used | 189 |
| abstract_inverted_index.were | 101, 106, 122, 174, 188, 243 |
| abstract_inverted_index.when | 147 |
| abstract_inverted_index.will | 250 |
| abstract_inverted_index.with | 108, 159 |
| abstract_inverted_index.>2 | 78 |
| abstract_inverted_index.(CXR) | 5 |
| abstract_inverted_index.2022. | 89 |
| abstract_inverted_index.Model | 90 |
| abstract_inverted_index.X-ray | 4 |
| abstract_inverted_index.acted | 149 |
| abstract_inverted_index.aimed | 48 |
| abstract_inverted_index.begin | 41 |
| abstract_inverted_index.chest | 3 |
| abstract_inverted_index.eight | 199 |
| abstract_inverted_index.final | 113 |
| abstract_inverted_index.study | 93, 180 |
| abstract_inverted_index.these | 39 |
| abstract_inverted_index.three | 204 |
| abstract_inverted_index.tools | 40 |
| abstract_inverted_index.train | 191 |
| abstract_inverted_index.while | 167, 202 |
| abstract_inverted_index.Device | 155 |
| abstract_inverted_index.assist | 16 |
| abstract_inverted_index.create | 11 |
| abstract_inverted_index.images | 187 |
| abstract_inverted_index.models | 116, 148, 207 |
| abstract_inverted_index.modern | 30 |
| abstract_inverted_index.review | 47, 215 |
| abstract_inverted_index.search | 64 |
| abstract_inverted_index.strong | 118 |
| abstract_inverted_index.128,662 | 186 |
| abstract_inverted_index.January | 85 |
| abstract_inverted_index.Several | 241 |
| abstract_inverted_index.between | 84 |
| abstract_inverted_index.capable | 75 |
| abstract_inverted_index.details | 91 |
| abstract_inverted_index.device. | 154 |
| abstract_inverted_index.devices | 220 |
| abstract_inverted_index.driving | 254 |
| abstract_inverted_index.effects | 168 |
| abstract_inverted_index.finding | 142 |
| abstract_inverted_index.improve | 19, 228, 235 |
| abstract_inverted_index.machine | 12, 31, 54, 72, 218, 261 |
| abstract_inverted_index.models. | 194 |
| abstract_inverted_index.perform | 226 |
| abstract_inverted_index.provide | 50 |
| abstract_inverted_index.quality | 259 |
| abstract_inverted_index.review. | 114 |
| abstract_inverted_index.studies | 135 |
| abstract_inverted_index.systems | 14, 33 |
| abstract_inverted_index.Multiple | 134 |
| abstract_inverted_index.articles | 105 |
| abstract_inverted_index.attempts | 9 |
| abstract_inverted_index.average, | 185 |
| abstract_inverted_index.clinical | 141, 170, 200 |
| abstract_inverted_index.compared | 158 |
| abstract_inverted_index.designed | 57, 221 |
| abstract_inverted_index.executed | 67 |
| abstract_inverted_index.findings | 80 |
| abstract_inverted_index.identify | 69 |
| abstract_inverted_index.included | 110 |
| abstract_inverted_index.learning | 13, 32, 55, 73, 219, 262 |
| abstract_inverted_index.overview | 52 |
| abstract_inverted_index.permeate | 43 |
| abstract_inverted_index.quality, | 100 |
| abstract_inverted_index.research | 70 |
| abstract_inverted_index.resulted | 7 |
| abstract_inverted_index.strategy | 65 |
| abstract_inverted_index.studies, | 166 |
| abstract_inverted_index.suggests | 216 |
| abstract_inverted_index.systems. | 263 |
| abstract_inverted_index.validate | 193 |
| abstract_inverted_index.Published | 115 |
| abstract_inverted_index.September | 88 |
| abstract_inverted_index.accuracy. | 21 |
| abstract_inverted_index.accurate, | 125, 128 |
| abstract_inverted_index.clinician | 246 |
| abstract_inverted_index.detecting | 77 |
| abstract_inverted_index.detection | 230 |
| abstract_inverted_index.diagnosis | 173 |
| abstract_inverted_index.evaluated | 175 |
| abstract_inverted_index.expertise | 249 |
| abstract_inverted_index.findings, | 201 |
| abstract_inverted_index.findings. | 213 |
| abstract_inverted_index.including | 95 |
| abstract_inverted_index.necessary | 35 |
| abstract_inverted_index.practice. | 44 |
| abstract_inverted_index.published | 83 |
| abstract_inverted_index.radiology | 239 |
| abstract_inverted_index.strongly, | 227 |
| abstract_inverted_index.typically | 123 |
| abstract_inverted_index.workflow. | 240 |
| abstract_inverted_index.Initially, | 103 |
| abstract_inverted_index.algorithms | 74 |
| abstract_inverted_index.assistance | 153 |
| abstract_inverted_index.classified | 196, 208 |
| abstract_inverted_index.clinicians | 17, 37, 146, 162 |
| abstract_inverted_index.diagnostic | 152 |
| abstract_inverted_index.efficiency | 237 |
| abstract_inverted_index.facilitate | 59, 223 |
| abstract_inverted_index.perception | 171 |
| abstract_inverted_index.retrieved, | 107 |
| abstract_inverted_index.standalone | 119 |
| abstract_inverted_index.systematic | 46, 63 |
| abstract_inverted_index.Limitations | 0 |
| abstract_inverted_index.clinicians, | 233 |
| abstract_inverted_index.clinicians. | 133 |
| abstract_inverted_index.identified, | 244 |
| abstract_inverted_index.improvement | 138 |
| abstract_inverted_index.involvement | 247 |
| abstract_inverted_index.limitations | 28, 242 |
| abstract_inverted_index.performance | 120, 144, 156, 231 |
| abstract_inverted_index.summarized. | 102 |
| abstract_inverted_index.applications | 56 |
| abstract_inverted_index.capabilities | 26 |
| abstract_inverted_index.demonstrated | 117, 136 |
| abstract_inverted_index.radiographic | 79 |
| abstract_inverted_index.radiologists | 130 |
| abstract_inverted_index.comprehensive | 206 |
| abstract_inverted_index.prospectively | 182 |
| abstract_inverted_index.understanding | 23 |
| abstract_inverted_index.classification | 143 |
| abstract_inverted_index.implementation | 257 |
| abstract_inverted_index.interpretation | 20, 225 |
| abstract_inverted_index.interpretation. | 61 |
| abstract_inverted_index.non-radiologist | 132 |
| abstract_inverted_index.characteristics, | 94 |
| cited_by_percentile_year.max | 99 |
| cited_by_percentile_year.min | 98 |
| corresponding_author_ids | https://openalex.org/A5090336817 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 15 |
| corresponding_institution_ids | https://openalex.org/I2800079252 |
| citation_normalized_percentile.value | 0.97921635 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |