Characterizing Subpopulations with Better Response to Treatment Using Observational Data – an Epilepsy Case Study Article Swipe
Michal Ozery-Flato
,
Tal El‐Hay
,
Ranit Aharonov
,
Naama Parush-Shear-Yashuv
,
Yaara Goldschmidt
,
Simon Borghs
,
Jane Chan
,
Nassim Haddad
,
Bosny Pierre‐Louis
,
Linda Kalilani
·
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.1101/290585
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.1101/290585
Electronic health records and health insurance claims, providing observational data on millions of patients, offer great opportunities, and challenges, for population health studies. The objective of this study is identifying subpopulations that are likely to benefit from a given treatment using observational data. We refer to these subpopulations as “better responders” and focus on characterizing these using linear scores with a limited number of variables. Building upon well-established causal inference techniques for analyzing observational data, we propose two algorithms that generate such scores for identifying better responders, as well as methods for evaluating and comparing these scores. We applied our methodology to a large dataset of ~135,000 epilepsy patients derived from claims data. Out of this sample, 85,000 were used to characterize subpopulations with better response to next-generation (“Newer”) anti-epileptic drugs (AEDs), compared to an alternative treatment by first-generation (“Older”) AEDs. The remaining 50,000 epilepsy patients were then used to evaluate our scores. Our results demonstrate the ability of our scores to identify large subpopulations of epilepsy patients with significantly better response to newer AEDs.
Related Topics
Concepts
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1101/290585
- https://www.biorxiv.org/content/biorxiv/early/2018/12/02/290585.full.pdf
- OA Status
- green
- Cited By
- 5
- References
- 39
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2795198907
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W2795198907Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1101/290585Digital Object Identifier
- Title
-
Characterizing Subpopulations with Better Response to Treatment Using Observational Data – an Epilepsy Case StudyWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2018Year of publication
- Publication date
-
2018-03-29Full publication date if available
- Authors
-
Michal Ozery-Flato, Tal El‐Hay, Ranit Aharonov, Naama Parush-Shear-Yashuv, Yaara Goldschmidt, Simon Borghs, Jane Chan, Nassim Haddad, Bosny Pierre‐Louis, Linda KalilaniList of authors in order
- Landing page
-
https://doi.org/10.1101/290585Publisher landing page
- PDF URL
-
https://www.biorxiv.org/content/biorxiv/early/2018/12/02/290585.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.biorxiv.org/content/biorxiv/early/2018/12/02/290585.full.pdfDirect OA link when available
- Concepts
-
Observational study, Epilepsy, Causal inference, Inference, Medicine, Population, Health records, Computer science, Artificial intelligence, Health care, Psychiatry, Internal medicine, Pathology, Economics, Economic growth, Environmental healthTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
5Total citation count in OpenAlex
- Citations by year (recent)
-
2021: 1, 2020: 3, 2018: 1Per-year citation counts (last 5 years)
- References (count)
-
39Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W2795198907 |
|---|---|
| doi | https://doi.org/10.1101/290585 |
| ids.doi | https://doi.org/10.1101/290585 |
| ids.mag | 2795198907 |
| ids.openalex | https://openalex.org/W2795198907 |
| fwci | 1.57172546 |
| type | preprint |
| title | Characterizing Subpopulations with Better Response to Treatment Using Observational Data – an Epilepsy Case Study |
| biblio.issue | |
| biblio.volume | |
| biblio.last_page | |
| biblio.first_page | |
| topics[0].id | https://openalex.org/T10845 |
| topics[0].field.id | https://openalex.org/fields/26 |
| topics[0].field.display_name | Mathematics |
| topics[0].score | 0.9998999834060669 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/2613 |
| topics[0].subfield.display_name | Statistics and Probability |
| topics[0].display_name | Advanced Causal Inference Techniques |
| topics[1].id | https://openalex.org/T11235 |
| topics[1].field.id | https://openalex.org/fields/26 |
| topics[1].field.display_name | Mathematics |
| topics[1].score | 0.9972000122070312 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/2613 |
| topics[1].subfield.display_name | Statistics and Probability |
| topics[1].display_name | Statistical Methods in Clinical Trials |
| topics[2].id | https://openalex.org/T10243 |
| topics[2].field.id | https://openalex.org/fields/26 |
| topics[2].field.display_name | Mathematics |
| topics[2].score | 0.9955000281333923 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/2613 |
| topics[2].subfield.display_name | Statistics and Probability |
| topics[2].display_name | Statistical Methods and Bayesian Inference |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C23131810 |
| concepts[0].level | 2 |
| concepts[0].score | 0.9403237700462341 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q818574 |
| concepts[0].display_name | Observational study |
| concepts[1].id | https://openalex.org/C2778186239 |
| concepts[1].level | 2 |
| concepts[1].score | 0.7480614185333252 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q41571 |
| concepts[1].display_name | Epilepsy |
| concepts[2].id | https://openalex.org/C158600405 |
| concepts[2].level | 2 |
| concepts[2].score | 0.73822021484375 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q5054566 |
| concepts[2].display_name | Causal inference |
| concepts[3].id | https://openalex.org/C2776214188 |
| concepts[3].level | 2 |
| concepts[3].score | 0.5310647487640381 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q408386 |
| concepts[3].display_name | Inference |
| concepts[4].id | https://openalex.org/C71924100 |
| concepts[4].level | 0 |
| concepts[4].score | 0.5061210989952087 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q11190 |
| concepts[4].display_name | Medicine |
| concepts[5].id | https://openalex.org/C2908647359 |
| concepts[5].level | 2 |
| concepts[5].score | 0.4628068804740906 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q2625603 |
| concepts[5].display_name | Population |
| concepts[6].id | https://openalex.org/C3019952477 |
| concepts[6].level | 3 |
| concepts[6].score | 0.4390102028846741 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q1324077 |
| concepts[6].display_name | Health records |
| concepts[7].id | https://openalex.org/C41008148 |
| concepts[7].level | 0 |
| concepts[7].score | 0.3719382882118225 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[7].display_name | Computer science |
| concepts[8].id | https://openalex.org/C154945302 |
| concepts[8].level | 1 |
| concepts[8].score | 0.24606630206108093 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[8].display_name | Artificial intelligence |
| concepts[9].id | https://openalex.org/C160735492 |
| concepts[9].level | 2 |
| concepts[9].score | 0.23095771670341492 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q31207 |
| concepts[9].display_name | Health care |
| concepts[10].id | https://openalex.org/C118552586 |
| concepts[10].level | 1 |
| concepts[10].score | 0.18969520926475525 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q7867 |
| concepts[10].display_name | Psychiatry |
| concepts[11].id | https://openalex.org/C126322002 |
| concepts[11].level | 1 |
| concepts[11].score | 0.14098963141441345 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q11180 |
| concepts[11].display_name | Internal medicine |
| concepts[12].id | https://openalex.org/C142724271 |
| concepts[12].level | 1 |
| concepts[12].score | 0.09783923625946045 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q7208 |
| concepts[12].display_name | Pathology |
| concepts[13].id | https://openalex.org/C162324750 |
| concepts[13].level | 0 |
| concepts[13].score | 0.0 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q8134 |
| concepts[13].display_name | Economics |
| concepts[14].id | https://openalex.org/C50522688 |
| concepts[14].level | 1 |
| concepts[14].score | 0.0 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q189833 |
| concepts[14].display_name | Economic growth |
| concepts[15].id | https://openalex.org/C99454951 |
| concepts[15].level | 1 |
| concepts[15].score | 0.0 |
| concepts[15].wikidata | https://www.wikidata.org/wiki/Q932068 |
| concepts[15].display_name | Environmental health |
| keywords[0].id | https://openalex.org/keywords/observational-study |
| keywords[0].score | 0.9403237700462341 |
| keywords[0].display_name | Observational study |
| keywords[1].id | https://openalex.org/keywords/epilepsy |
| keywords[1].score | 0.7480614185333252 |
| keywords[1].display_name | Epilepsy |
| keywords[2].id | https://openalex.org/keywords/causal-inference |
| keywords[2].score | 0.73822021484375 |
| keywords[2].display_name | Causal inference |
| keywords[3].id | https://openalex.org/keywords/inference |
| keywords[3].score | 0.5310647487640381 |
| keywords[3].display_name | Inference |
| keywords[4].id | https://openalex.org/keywords/medicine |
| keywords[4].score | 0.5061210989952087 |
| keywords[4].display_name | Medicine |
| keywords[5].id | https://openalex.org/keywords/population |
| keywords[5].score | 0.4628068804740906 |
| keywords[5].display_name | Population |
| keywords[6].id | https://openalex.org/keywords/health-records |
| keywords[6].score | 0.4390102028846741 |
| keywords[6].display_name | Health records |
| keywords[7].id | https://openalex.org/keywords/computer-science |
| keywords[7].score | 0.3719382882118225 |
| keywords[7].display_name | Computer science |
| keywords[8].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[8].score | 0.24606630206108093 |
| keywords[8].display_name | Artificial intelligence |
| keywords[9].id | https://openalex.org/keywords/health-care |
| keywords[9].score | 0.23095771670341492 |
| keywords[9].display_name | Health care |
| keywords[10].id | https://openalex.org/keywords/psychiatry |
| keywords[10].score | 0.18969520926475525 |
| keywords[10].display_name | Psychiatry |
| keywords[11].id | https://openalex.org/keywords/internal-medicine |
| keywords[11].score | 0.14098963141441345 |
| keywords[11].display_name | Internal medicine |
| keywords[12].id | https://openalex.org/keywords/pathology |
| keywords[12].score | 0.09783923625946045 |
| keywords[12].display_name | Pathology |
| language | en |
| locations[0].id | doi:10.1101/290585 |
| 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 | |
| locations[0].pdf_url | https://www.biorxiv.org/content/biorxiv/early/2018/12/02/290585.full.pdf |
| locations[0].version | acceptedVersion |
| locations[0].raw_type | posted-content |
| locations[0].license_id | |
| locations[0].is_accepted | True |
| locations[0].is_published | False |
| locations[0].raw_source_name | |
| locations[0].landing_page_url | https://doi.org/10.1101/290585 |
| indexed_in | crossref |
| authorships[0].author.id | https://openalex.org/A5018121200 |
| authorships[0].author.orcid | https://orcid.org/0000-0002-8223-7989 |
| authorships[0].author.display_name | Michal Ozery-Flato |
| authorships[0].countries | IL |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I4210167297 |
| authorships[0].affiliations[0].raw_affiliation_string | IBM Research-Haifa, Haifa University Campus, Mount Carmel Haifa, 3498825, Israel (email: , , , , ). |
| authorships[0].institutions[0].id | https://openalex.org/I4210167297 |
| authorships[0].institutions[0].ror | https://ror.org/05rw9t746 |
| authorships[0].institutions[0].type | facility |
| authorships[0].institutions[0].lineage | https://openalex.org/I1341412227, https://openalex.org/I4210114115, https://openalex.org/I4210167297 |
| authorships[0].institutions[0].country_code | IL |
| authorships[0].institutions[0].display_name | IBM Research - Haifa |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Michal Ozery-Flato |
| authorships[0].is_corresponding | True |
| authorships[0].raw_affiliation_strings | IBM Research-Haifa, Haifa University Campus, Mount Carmel Haifa, 3498825, Israel (email: , , , , ). |
| authorships[1].author.id | https://openalex.org/A5010534760 |
| authorships[1].author.orcid | https://orcid.org/0000-0002-2156-1558 |
| authorships[1].author.display_name | Tal El‐Hay |
| authorships[1].countries | IL |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I4210167297 |
| authorships[1].affiliations[0].raw_affiliation_string | IBM Research-Haifa, Haifa University Campus, Mount Carmel Haifa, 3498825, Israel (email: , , , , ). |
| authorships[1].institutions[0].id | https://openalex.org/I4210167297 |
| authorships[1].institutions[0].ror | https://ror.org/05rw9t746 |
| authorships[1].institutions[0].type | facility |
| authorships[1].institutions[0].lineage | https://openalex.org/I1341412227, https://openalex.org/I4210114115, https://openalex.org/I4210167297 |
| authorships[1].institutions[0].country_code | IL |
| authorships[1].institutions[0].display_name | IBM Research - Haifa |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Tal El-Hay |
| authorships[1].is_corresponding | True |
| authorships[1].raw_affiliation_strings | IBM Research-Haifa, Haifa University Campus, Mount Carmel Haifa, 3498825, Israel (email: , , , , ). |
| authorships[2].author.id | https://openalex.org/A5035493244 |
| authorships[2].author.orcid | |
| authorships[2].author.display_name | Ranit Aharonov |
| authorships[2].countries | IL |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I4210167297 |
| authorships[2].affiliations[0].raw_affiliation_string | IBM Research-Haifa, Haifa University Campus, Mount Carmel Haifa, 3498825, Israel (email: , , , , ). |
| authorships[2].institutions[0].id | https://openalex.org/I4210167297 |
| authorships[2].institutions[0].ror | https://ror.org/05rw9t746 |
| authorships[2].institutions[0].type | facility |
| authorships[2].institutions[0].lineage | https://openalex.org/I1341412227, https://openalex.org/I4210114115, https://openalex.org/I4210167297 |
| authorships[2].institutions[0].country_code | IL |
| authorships[2].institutions[0].display_name | IBM Research - Haifa |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Ranit Aharonov |
| authorships[2].is_corresponding | True |
| authorships[2].raw_affiliation_strings | IBM Research-Haifa, Haifa University Campus, Mount Carmel Haifa, 3498825, Israel (email: , , , , ). |
| authorships[3].author.id | https://openalex.org/A5076255663 |
| authorships[3].author.orcid | |
| authorships[3].author.display_name | Naama Parush-Shear-Yashuv |
| authorships[3].countries | IL |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I4210167297 |
| authorships[3].affiliations[0].raw_affiliation_string | IBM Research-Haifa, Haifa University Campus, Mount Carmel Haifa, 3498825, Israel (email: , , , , ). |
| authorships[3].institutions[0].id | https://openalex.org/I4210167297 |
| authorships[3].institutions[0].ror | https://ror.org/05rw9t746 |
| authorships[3].institutions[0].type | facility |
| authorships[3].institutions[0].lineage | https://openalex.org/I1341412227, https://openalex.org/I4210114115, https://openalex.org/I4210167297 |
| authorships[3].institutions[0].country_code | IL |
| authorships[3].institutions[0].display_name | IBM Research - Haifa |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Naama Parush-Shear-Yashuv |
| authorships[3].is_corresponding | True |
| authorships[3].raw_affiliation_strings | IBM Research-Haifa, Haifa University Campus, Mount Carmel Haifa, 3498825, Israel (email: , , , , ). |
| authorships[4].author.id | https://openalex.org/A5011087438 |
| authorships[4].author.orcid | https://orcid.org/0000-0002-1294-870X |
| authorships[4].author.display_name | Yaara Goldschmidt |
| authorships[4].countries | IL |
| authorships[4].affiliations[0].institution_ids | https://openalex.org/I4210167297 |
| authorships[4].affiliations[0].raw_affiliation_string | IBM Research-Haifa, Haifa University Campus, Mount Carmel Haifa, 3498825, Israel (email: , , , , ). |
| authorships[4].institutions[0].id | https://openalex.org/I4210167297 |
| authorships[4].institutions[0].ror | https://ror.org/05rw9t746 |
| authorships[4].institutions[0].type | facility |
| authorships[4].institutions[0].lineage | https://openalex.org/I1341412227, https://openalex.org/I4210114115, https://openalex.org/I4210167297 |
| authorships[4].institutions[0].country_code | IL |
| authorships[4].institutions[0].display_name | IBM Research - Haifa |
| authorships[4].author_position | middle |
| authorships[4].raw_author_name | Yaara Goldschmidt |
| authorships[4].is_corresponding | True |
| authorships[4].raw_affiliation_strings | IBM Research-Haifa, Haifa University Campus, Mount Carmel Haifa, 3498825, Israel (email: , , , , ). |
| authorships[5].author.id | https://openalex.org/A5079889841 |
| authorships[5].author.orcid | https://orcid.org/0000-0003-1081-7981 |
| authorships[5].author.display_name | Simon Borghs |
| authorships[5].countries | GB |
| authorships[5].affiliations[0].institution_ids | https://openalex.org/I4210134054 |
| authorships[5].affiliations[0].raw_affiliation_string | UCB Pharma, 08 Bath Road, SL1 3WE, Slough, UK (email: , ). |
| authorships[5].institutions[0].id | https://openalex.org/I4210134054 |
| authorships[5].institutions[0].ror | https://ror.org/03428qp74 |
| authorships[5].institutions[0].type | company |
| authorships[5].institutions[0].lineage | https://openalex.org/I4210134054, https://openalex.org/I85722119 |
| authorships[5].institutions[0].country_code | GB |
| authorships[5].institutions[0].display_name | UCB Pharma (United Kingdom) |
| authorships[5].author_position | middle |
| authorships[5].raw_author_name | Simon Borghs |
| authorships[5].is_corresponding | True |
| authorships[5].raw_affiliation_strings | UCB Pharma, 08 Bath Road, SL1 3WE, Slough, UK (email: , ). |
| authorships[6].author.id | https://openalex.org/A5044515238 |
| authorships[6].author.orcid | |
| authorships[6].author.display_name | Jane Chan |
| authorships[6].countries | GB |
| authorships[6].affiliations[0].institution_ids | https://openalex.org/I4210134054 |
| authorships[6].affiliations[0].raw_affiliation_string | UCB Pharma, 08 Bath Road, SL1 3WE, Slough, UK (email: , ). |
| authorships[6].institutions[0].id | https://openalex.org/I4210134054 |
| authorships[6].institutions[0].ror | https://ror.org/03428qp74 |
| authorships[6].institutions[0].type | company |
| authorships[6].institutions[0].lineage | https://openalex.org/I4210134054, https://openalex.org/I85722119 |
| authorships[6].institutions[0].country_code | GB |
| authorships[6].institutions[0].display_name | UCB Pharma (United Kingdom) |
| authorships[6].author_position | middle |
| authorships[6].raw_author_name | Jane Chan |
| authorships[6].is_corresponding | True |
| authorships[6].raw_affiliation_strings | UCB Pharma, 08 Bath Road, SL1 3WE, Slough, UK (email: , ). |
| authorships[7].author.id | https://openalex.org/A5032608900 |
| authorships[7].author.orcid | |
| authorships[7].author.display_name | Nassim Haddad |
| authorships[7].countries | BE |
| authorships[7].affiliations[0].institution_ids | https://openalex.org/I85722119 |
| authorships[7].affiliations[0].raw_affiliation_string | UCB Biopharma, Allée de la Recherche 60, 1070 Anderlecht, Belgium (email: ). |
| authorships[7].institutions[0].id | https://openalex.org/I85722119 |
| authorships[7].institutions[0].ror | https://ror.org/01n029866 |
| authorships[7].institutions[0].type | company |
| authorships[7].institutions[0].lineage | https://openalex.org/I85722119 |
| authorships[7].institutions[0].country_code | BE |
| authorships[7].institutions[0].display_name | UCB Pharma (Belgium) |
| authorships[7].author_position | middle |
| authorships[7].raw_author_name | Nassim Haddad |
| authorships[7].is_corresponding | True |
| authorships[7].raw_affiliation_strings | UCB Biopharma, Allée de la Recherche 60, 1070 Anderlecht, Belgium (email: ). |
| authorships[8].author.id | https://openalex.org/A5012312684 |
| authorships[8].author.orcid | |
| authorships[8].author.display_name | Bosny Pierre‐Louis |
| authorships[8].affiliations[0].raw_affiliation_string | UCB Biosciences Inc., 8010 Arco Corporate Drive, Raleigh, NC 27617 USA (email: , ). |
| authorships[8].author_position | middle |
| authorships[8].raw_author_name | Bosny Pierre-Louis |
| authorships[8].is_corresponding | True |
| authorships[8].raw_affiliation_strings | UCB Biosciences Inc., 8010 Arco Corporate Drive, Raleigh, NC 27617 USA (email: , ). |
| authorships[9].author.id | https://openalex.org/A5086622773 |
| authorships[9].author.orcid | https://orcid.org/0000-0003-2820-0875 |
| authorships[9].author.display_name | Linda Kalilani |
| authorships[9].affiliations[0].raw_affiliation_string | UCB Biosciences Inc., 8010 Arco Corporate Drive, Raleigh, NC 27617 USA (email: , ). |
| authorships[9].author_position | last |
| authorships[9].raw_author_name | Linda Kalilani |
| authorships[9].is_corresponding | True |
| authorships[9].raw_affiliation_strings | UCB Biosciences Inc., 8010 Arco Corporate Drive, Raleigh, NC 27617 USA (email: , ). |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://www.biorxiv.org/content/biorxiv/early/2018/12/02/290585.full.pdf |
| open_access.oa_status | green |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Characterizing Subpopulations with Better Response to Treatment Using Observational Data – an Epilepsy Case Study |
| has_fulltext | True |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T10845 |
| primary_topic.field.id | https://openalex.org/fields/26 |
| primary_topic.field.display_name | Mathematics |
| primary_topic.score | 0.9998999834060669 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/2613 |
| primary_topic.subfield.display_name | Statistics and Probability |
| primary_topic.display_name | Advanced Causal Inference Techniques |
| related_works | https://openalex.org/W2979832559, https://openalex.org/W3128129045, https://openalex.org/W4385077270, https://openalex.org/W4387531643, https://openalex.org/W4324300609, https://openalex.org/W2997970376, https://openalex.org/W4231150422, https://openalex.org/W3164869265, https://openalex.org/W4248255116, https://openalex.org/W4307156845 |
| cited_by_count | 5 |
| counts_by_year[0].year | 2021 |
| counts_by_year[0].cited_by_count | 1 |
| counts_by_year[1].year | 2020 |
| counts_by_year[1].cited_by_count | 3 |
| counts_by_year[2].year | 2018 |
| counts_by_year[2].cited_by_count | 1 |
| locations_count | 1 |
| best_oa_location.id | doi:10.1101/290585 |
| 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 | |
| best_oa_location.pdf_url | https://www.biorxiv.org/content/biorxiv/early/2018/12/02/290585.full.pdf |
| best_oa_location.version | acceptedVersion |
| best_oa_location.raw_type | posted-content |
| best_oa_location.license_id | |
| 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/10.1101/290585 |
| primary_location.id | doi:10.1101/290585 |
| 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 | |
| primary_location.pdf_url | https://www.biorxiv.org/content/biorxiv/early/2018/12/02/290585.full.pdf |
| primary_location.version | acceptedVersion |
| primary_location.raw_type | posted-content |
| primary_location.license_id | |
| primary_location.is_accepted | True |
| primary_location.is_published | False |
| primary_location.raw_source_name | |
| primary_location.landing_page_url | https://doi.org/10.1101/290585 |
| publication_date | 2018-03-29 |
| publication_year | 2018 |
| referenced_works | https://openalex.org/W2026967508, https://openalex.org/W2036193982, https://openalex.org/W2548641835, https://openalex.org/W2605397892, https://openalex.org/W2153646525, https://openalex.org/W2039414656, https://openalex.org/W2161239183, https://openalex.org/W2015182866, https://openalex.org/W2305754340, https://openalex.org/W2603536356, https://openalex.org/W2140792819, https://openalex.org/W1573833177, https://openalex.org/W2150291618, https://openalex.org/W2009187570, https://openalex.org/W2135738480, https://openalex.org/W1994731067, https://openalex.org/W1984454461, https://openalex.org/W2168458505, https://openalex.org/W2135046866, https://openalex.org/W2787894218, https://openalex.org/W2181470043, https://openalex.org/W2143117649, https://openalex.org/W2064903582, https://openalex.org/W2028040032, https://openalex.org/W3122812581, https://openalex.org/W2132324013, https://openalex.org/W2120817734, https://openalex.org/W2787023317, https://openalex.org/W6840927081, https://openalex.org/W2734806315, https://openalex.org/W2963728224, https://openalex.org/W2286797211, https://openalex.org/W606561187, https://openalex.org/W2185922570, https://openalex.org/W2964115178, https://openalex.org/W2962695761, https://openalex.org/W1554944419, https://openalex.org/W2092483401, https://openalex.org/W2970567995 |
| referenced_works_count | 39 |
| abstract_inverted_index.a | 38, 61, 103 |
| abstract_inverted_index.We | 44, 98 |
| abstract_inverted_index.an | 135 |
| abstract_inverted_index.as | 49, 88, 90 |
| abstract_inverted_index.by | 138 |
| abstract_inverted_index.is | 29 |
| abstract_inverted_index.of | 13, 26, 64, 106, 115, 159, 166 |
| abstract_inverted_index.on | 11, 54 |
| abstract_inverted_index.to | 35, 46, 102, 121, 127, 134, 150, 162, 173 |
| abstract_inverted_index.we | 76 |
| abstract_inverted_index.Our | 154 |
| abstract_inverted_index.Out | 114 |
| abstract_inverted_index.The | 24, 142 |
| abstract_inverted_index.and | 4, 18, 52, 94 |
| abstract_inverted_index.are | 33 |
| abstract_inverted_index.for | 20, 72, 84, 92 |
| abstract_inverted_index.our | 100, 152, 160 |
| abstract_inverted_index.the | 157 |
| abstract_inverted_index.two | 78 |
| abstract_inverted_index.data | 10 |
| abstract_inverted_index.from | 37, 111 |
| abstract_inverted_index.such | 82 |
| abstract_inverted_index.that | 32, 80 |
| abstract_inverted_index.then | 148 |
| abstract_inverted_index.this | 27, 116 |
| abstract_inverted_index.upon | 67 |
| abstract_inverted_index.used | 120, 149 |
| abstract_inverted_index.well | 89 |
| abstract_inverted_index.were | 119, 147 |
| abstract_inverted_index.with | 60, 124, 169 |
| abstract_inverted_index.AEDs. | 141, 175 |
| abstract_inverted_index.data, | 75 |
| abstract_inverted_index.data. | 43, 113 |
| abstract_inverted_index.drugs | 131 |
| abstract_inverted_index.focus | 53 |
| abstract_inverted_index.given | 39 |
| abstract_inverted_index.great | 16 |
| abstract_inverted_index.large | 104, 164 |
| abstract_inverted_index.newer | 174 |
| abstract_inverted_index.offer | 15 |
| abstract_inverted_index.refer | 45 |
| abstract_inverted_index.study | 28 |
| abstract_inverted_index.these | 47, 56, 96 |
| abstract_inverted_index.using | 41, 57 |
| abstract_inverted_index.50,000 | 144 |
| abstract_inverted_index.85,000 | 118 |
| abstract_inverted_index.better | 86, 125, 171 |
| abstract_inverted_index.causal | 69 |
| abstract_inverted_index.claims | 112 |
| abstract_inverted_index.health | 2, 5, 22 |
| abstract_inverted_index.likely | 34 |
| abstract_inverted_index.linear | 58 |
| abstract_inverted_index.number | 63 |
| abstract_inverted_index.scores | 59, 83, 161 |
| abstract_inverted_index.(AEDs), | 132 |
| abstract_inverted_index.ability | 158 |
| abstract_inverted_index.applied | 99 |
| abstract_inverted_index.benefit | 36 |
| abstract_inverted_index.claims, | 7 |
| abstract_inverted_index.dataset | 105 |
| abstract_inverted_index.derived | 110 |
| abstract_inverted_index.limited | 62 |
| abstract_inverted_index.methods | 91 |
| abstract_inverted_index.propose | 77 |
| abstract_inverted_index.records | 3 |
| abstract_inverted_index.results | 155 |
| abstract_inverted_index.sample, | 117 |
| abstract_inverted_index.scores. | 97, 153 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.Building | 66 |
| abstract_inverted_index.compared | 133 |
| abstract_inverted_index.epilepsy | 108, 145, 167 |
| abstract_inverted_index.evaluate | 151 |
| abstract_inverted_index.generate | 81 |
| abstract_inverted_index.identify | 163 |
| abstract_inverted_index.millions | 12 |
| abstract_inverted_index.patients | 109, 146, 168 |
| abstract_inverted_index.response | 126, 172 |
| abstract_inverted_index.studies. | 23 |
| abstract_inverted_index.~135,000 | 107 |
| abstract_inverted_index.analyzing | 73 |
| abstract_inverted_index.comparing | 95 |
| abstract_inverted_index.inference | 70 |
| abstract_inverted_index.insurance | 6 |
| abstract_inverted_index.objective | 25 |
| abstract_inverted_index.patients, | 14 |
| abstract_inverted_index.providing | 8 |
| abstract_inverted_index.remaining | 143 |
| abstract_inverted_index.treatment | 40, 137 |
| abstract_inverted_index.“better | 50 |
| abstract_inverted_index.Electronic | 1 |
| abstract_inverted_index.algorithms | 79 |
| abstract_inverted_index.evaluating | 93 |
| abstract_inverted_index.population | 21 |
| abstract_inverted_index.techniques | 71 |
| abstract_inverted_index.variables. | 65 |
| abstract_inverted_index.alternative | 136 |
| abstract_inverted_index.challenges, | 19 |
| abstract_inverted_index.demonstrate | 156 |
| abstract_inverted_index.identifying | 30, 85 |
| abstract_inverted_index.methodology | 101 |
| abstract_inverted_index.responders, | 87 |
| abstract_inverted_index.characterize | 122 |
| abstract_inverted_index.(“Newer”) | 129 |
| abstract_inverted_index.(“Older”) | 140 |
| abstract_inverted_index.observational | 9, 42, 74 |
| abstract_inverted_index.responders” | 51 |
| abstract_inverted_index.significantly | 170 |
| abstract_inverted_index.anti-epileptic | 130 |
| abstract_inverted_index.characterizing | 55 |
| abstract_inverted_index.opportunities, | 17 |
| abstract_inverted_index.subpopulations | 31, 48, 123, 165 |
| abstract_inverted_index.next-generation | 128 |
| abstract_inverted_index.first-generation | 139 |
| abstract_inverted_index.well-established | 68 |
| cited_by_percentile_year.max | 97 |
| cited_by_percentile_year.min | 89 |
| corresponding_author_ids | https://openalex.org/A5032608900, https://openalex.org/A5086622773, https://openalex.org/A5010534760, https://openalex.org/A5076255663, https://openalex.org/A5018121200, https://openalex.org/A5044515238, https://openalex.org/A5079889841, https://openalex.org/A5035493244, https://openalex.org/A5012312684, https://openalex.org/A5011087438 |
| countries_distinct_count | 3 |
| institutions_distinct_count | 10 |
| corresponding_institution_ids | https://openalex.org/I4210134054, https://openalex.org/I4210167297, https://openalex.org/I85722119 |
| citation_normalized_percentile.value | 0.80394874 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |