{"id":"https://openalex.org/W4403819889","doi":"https://doi.org/10.48550/arxiv.2410.00509","title":"Learning Personalized Treatment Decisions in Precision Medicine: Disentangling Treatment Assignment Bias in Counterfactual Outcome Prediction and Biomarker Identification","display_name":"Learning Personalized Treatment Decisions in Precision Medicine: Disentangling Treatment Assignment Bias in Counterfactual Outcome Prediction and Biomarker Identification","publication_year":2024,"publication_date":"2024-10-01","ids":{"openalex":"https://openalex.org/W4403819889","doi":"https://doi.org/10.48550/arxiv.2410.00509"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2410.00509","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2410.00509","pdf_url":"https://arxiv.org/pdf/2410.00509","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2410.00509","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5114427098","display_name":"Michael Vollenweider","orcid":"https://orcid.org/0000-0001-8193-7986"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Vollenweider, Michael","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071722406","display_name":"Manuel Sch\u00fcrch","orcid":"https://orcid.org/0000-0003-2175-2511"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sch\u00fcrch, Manuel","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034322501","display_name":"Christian R\u00f6hrer","orcid":"https://orcid.org/0000-0002-5631-205X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rohrer, Chiara","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049255125","display_name":"Gabriele Gut","orcid":"https://orcid.org/0000-0001-8991-0040"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gut, Gabriele","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025057284","display_name":"Michael Krauthammer","orcid":"https://orcid.org/0000-0002-4808-1845"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Krauthammer, Michael","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5012693904","display_name":"Andreas Wicki","orcid":"https://orcid.org/0000-0002-2924-8080"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wicki, Andreas","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5114427098"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.9878000020980835,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.9878000020980835,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11235","display_name":"Statistical Methods in Clinical Trials","score":0.9086999893188477,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10845","display_name":"Advanced Causal Inference Techniques","score":0.9014000296592712,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/counterfactual-thinking","display_name":"Counterfactual thinking","score":0.863438606262207},{"id":"https://openalex.org/keywords/precision-medicine","display_name":"Precision medicine","score":0.7757712602615356},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.6712769865989685},{"id":"https://openalex.org/keywords/biomarker","display_name":"Biomarker","score":0.6485328674316406},{"id":"https://openalex.org/keywords/outcome","display_name":"Outcome (game theory)","score":0.6196596622467041},{"id":"https://openalex.org/keywords/personalized-medicine","display_name":"Personalized medicine","score":0.5831695199012756},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.37482714653015137},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.36860477924346924},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.33187252283096313},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3287844657897949},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.324293315410614},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.30733567476272583},{"id":"https://openalex.org/keywords/bioinformatics","display_name":"Bioinformatics","score":0.19023990631103516},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.1755935549736023},{"id":"https://openalex.org/keywords/social-psychology","display_name":"Social psychology","score":0.1319812536239624},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.12465497851371765},{"id":"https://openalex.org/keywords/genetics","display_name":"Genetics","score":0.076192706823349}],"concepts":[{"id":"https://openalex.org/C108650721","wikidata":"https://www.wikidata.org/wiki/Q1783253","display_name":"Counterfactual thinking","level":2,"score":0.863438606262207},{"id":"https://openalex.org/C163763905","wikidata":"https://www.wikidata.org/wiki/Q17075943","display_name":"Precision medicine","level":2,"score":0.7757712602615356},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.6712769865989685},{"id":"https://openalex.org/C2781197716","wikidata":"https://www.wikidata.org/wiki/Q864574","display_name":"Biomarker","level":2,"score":0.6485328674316406},{"id":"https://openalex.org/C148220186","wikidata":"https://www.wikidata.org/wiki/Q7111912","display_name":"Outcome (game theory)","level":2,"score":0.6196596622467041},{"id":"https://openalex.org/C32220436","wikidata":"https://www.wikidata.org/wiki/Q2072214","display_name":"Personalized medicine","level":2,"score":0.5831695199012756},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.37482714653015137},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.36860477924346924},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.33187252283096313},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3287844657897949},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.324293315410614},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.30733567476272583},{"id":"https://openalex.org/C60644358","wikidata":"https://www.wikidata.org/wiki/Q128570","display_name":"Bioinformatics","level":1,"score":0.19023990631103516},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.1755935549736023},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.1319812536239624},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.12465497851371765},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.076192706823349},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C144237770","wikidata":"https://www.wikidata.org/wiki/Q747534","display_name":"Mathematical economics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2410.00509","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2410.00509","pdf_url":"https://arxiv.org/pdf/2410.00509","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2410.00509","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2410.00509","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2410.00509","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2410.00509","pdf_url":"https://arxiv.org/pdf/2410.00509","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4403819889.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W3163462160","https://openalex.org/W4210625552","https://openalex.org/W3082935376","https://openalex.org/W4399651953","https://openalex.org/W4386960999","https://openalex.org/W2899657781","https://openalex.org/W4322484660","https://openalex.org/W3193951088","https://openalex.org/W4388011470","https://openalex.org/W4230423494"],"abstract_inverted_index":{"Precision":[0],"medicine":[1],"has":[2],"the":[3,34,83,130,163,182],"potential":[4],"to":[5,9,26,142,152,166],"tailor":[6],"treatment":[7,46,73,86,185],"decisions":[8,186],"individual":[10],"patients":[11],"using":[12,49],"machine":[13],"learning":[14],"(ML)":[15],"and":[16,33,52,62,108,114],"artificial":[17],"intelligence":[18],"(AI),":[19],"but":[20],"it":[21],"faces":[22],"significant":[23],"challenges":[24],"due":[25],"complex":[27],"biases":[28,48,140,170],"in":[29,88,171,175,187],"clinical":[30,90,172],"observational":[31,85,173],"data":[32,174],"high-dimensional":[35],"nature":[36],"of":[37,45,82,132,184],"biological":[38,110,120],"data.":[39,134],"This":[40,161],"study":[41],"models":[42,58],"various":[43],"types":[44],"assignment":[47],"mutual":[50],"information":[51],"investigates":[53],"their":[54],"impact":[55],"on":[56,71,78,98,158],"ML":[57,177],"for":[59,168],"counterfactual":[60,67,176],"prediction":[61,159],"biomarker":[63],"identification.":[64],"Unlike":[65],"traditional":[66],"benchmarks":[68],"that":[69,128,138],"rely":[70],"fixed":[72],"policies,":[74],"our":[75,94],"work":[76],"focuses":[77],"modeling":[79],"different":[80,139],"characteristics":[81],"underlying":[84],"policy":[87],"distinct":[89],"settings.":[91],"We":[92],"validate":[93],"approach":[95],"through":[96],"experiments":[97],"toy":[99],"datasets,":[100],"semi-synthetic":[101],"tumor":[102],"cancer":[103],"genome":[104],"atlas":[105],"(TCGA)":[106],"data,":[107],"real-world":[109,133],"outcomes":[111],"from":[112],"drug":[113],"CRISPR":[115],"screens.":[116],"By":[117],"incorporating":[118],"empirical":[119],"mechanisms,":[121,154],"we":[122],"create":[123],"a":[124],"more":[125],"realistic":[126],"benchmark":[127],"reflects":[129],"complexities":[131],"Our":[135],"analysis":[136],"reveals":[137],"lead":[141],"varying":[143],"model":[144,178],"performances,":[145],"with":[146],"some":[147],"biases,":[148],"especially":[149],"those":[150],"unrelated":[151],"outcome":[153],"having":[155],"minimal":[156],"effect":[157],"accuracy.":[160],"highlights":[162],"crucial":[164],"need":[165],"account":[167],"specific":[169],"development,":[179],"ultimately":[180],"enhancing":[181],"personalization":[183],"precision":[188],"medicine.":[189]},"counts_by_year":[],"updated_date":"2026-03-11T14:59:36.786465","created_date":"2025-10-10T00:00:00"}