{"id":"https://openalex.org/W4387294167","doi":"https://doi.org/10.48550/arxiv.2309.17169","title":"An evaluation of GPT models for phenotype concept recognition","display_name":"An evaluation of GPT models for phenotype concept recognition","publication_year":2023,"publication_date":"2023-09-29","ids":{"openalex":"https://openalex.org/W4387294167","doi":"https://doi.org/10.48550/arxiv.2309.17169"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2309.17169","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2309.17169","pdf_url":"https://arxiv.org/pdf/2309.17169","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/2309.17169","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5011041769","display_name":"Tudor Groza","orcid":"https://orcid.org/0000-0003-2267-8333"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Groza, Tudor","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072638101","display_name":"Harry Caufield","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Caufield, Harry","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004979535","display_name":"Dylan Gration","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gration, Dylan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089939981","display_name":"Gareth Baynam","orcid":"https://orcid.org/0000-0003-4920-9553"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Baynam, Gareth","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064320417","display_name":"Melissa Haendel","orcid":"https://orcid.org/0000-0001-9114-8737"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Haendel, Melissa A","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033225381","display_name":"Peter N. Robinson","orcid":"https://orcid.org/0000-0002-0736-9199"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Robinson, Peter N","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002223413","display_name":"Chris Mungall","orcid":"https://orcid.org/0000-0002-6601-2165"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mungall, Christopher J","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5073533486","display_name":"Justin Reese","orcid":"https://orcid.org/0000-0002-2170-2250"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Reese, Justin T","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":8,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":1,"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/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.9800000190734863,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.9800000190734863,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.961899995803833,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9521999955177307,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.6866904497146606},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6443971395492554},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6299560070037842},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6052725911140442},{"id":"https://openalex.org/keywords/ontology","display_name":"Ontology","score":0.5221010446548462},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5038871169090271},{"id":"https://openalex.org/keywords/concordance","display_name":"Concordance","score":0.4705154001712799},{"id":"https://openalex.org/keywords/phenotype","display_name":"Phenotype","score":0.410102516412735},{"id":"https://openalex.org/keywords/bioinformatics","display_name":"Bioinformatics","score":0.2513647675514221},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.13247057795524597}],"concepts":[{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.6866904497146606},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6443971395492554},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6299560070037842},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6052725911140442},{"id":"https://openalex.org/C25810664","wikidata":"https://www.wikidata.org/wiki/Q44325","display_name":"Ontology","level":2,"score":0.5221010446548462},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5038871169090271},{"id":"https://openalex.org/C160798450","wikidata":"https://www.wikidata.org/wiki/Q4230870","display_name":"Concordance","level":2,"score":0.4705154001712799},{"id":"https://openalex.org/C127716648","wikidata":"https://www.wikidata.org/wiki/Q104053","display_name":"Phenotype","level":3,"score":0.410102516412735},{"id":"https://openalex.org/C60644358","wikidata":"https://www.wikidata.org/wiki/Q128570","display_name":"Bioinformatics","level":1,"score":0.2513647675514221},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.13247057795524597},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"pmh:oai:arXiv.org:2309.17169","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2309.17169","pdf_url":"https://arxiv.org/pdf/2309.17169","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":"pmh:ark:/13030/qt0ng965n7","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null},{"id":"pmh:oai:pure.atira.dk:publications/66071cfb-d40d-4c46-809f-1b22b0cbe646","is_oa":true,"landing_page_url":"https://research-repository.uwa.edu.au/en/publications/66071cfb-d40d-4c46-809f-1b22b0cbe646","pdf_url":null,"source":{"id":"https://openalex.org/S4306402523","display_name":"UWA Profiles and Research Repository (University of Western Australia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I177877127","host_organization_name":"The University of Western Australia","host_organization_lineage":["https://openalex.org/I177877127"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Groza , T , Caufield , H , Gration , D , Baynam , G , Haendel , M A , Robinson , P N , Mungall , C J & Reese , J T 2024 , ' An evaluation of GPT models for phenotype concept recognition ' , BMC Medical Informatics and Decision Making , vol. 24 , no. 1 , 30 . https://doi.org/10.1186/s12911-024-02439-w","raw_type":"article"},{"id":"doi:10.48550/arxiv.2309.17169","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2309.17169","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:2309.17169","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2309.17169","pdf_url":"https://arxiv.org/pdf/2309.17169","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":[{"id":"https://metadata.un.org/sdg/4","score":0.800000011920929,"display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G1976569787","display_name":null,"funder_award_id":"NHGRI RM1HG010860","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G33229909","display_name":null,"funder_award_id":"DE-AC0205CH1123","funder_id":"https://openalex.org/F4320337480","funder_display_name":"Basic Energy Sciences"},{"id":"https://openalex.org/G6029894467","display_name":null,"funder_award_id":"U24HG011449","funder_id":"https://openalex.org/F4320337348","funder_display_name":"National Human Genome Research Institute"},{"id":"https://openalex.org/G6032735710","display_name":null,"funder_award_id":"RM1HG010860","funder_id":"https://openalex.org/F4320337348","funder_display_name":"National Human Genome Research Institute"},{"id":"https://openalex.org/G8357141719","display_name":null,"funder_award_id":"DE-AC0205CH1123","funder_id":"https://openalex.org/F4320306084","funder_display_name":"U.S. Department of Energy"}],"funders":[{"id":"https://openalex.org/F4320306084","display_name":"U.S. Department of Energy","ror":"https://ror.org/01bj3aw27"},{"id":"https://openalex.org/F4320312688","display_name":"Children's Hospital Foundation","ror":null},{"id":"https://openalex.org/F4320315345","display_name":"McCusker Charitable Foundation","ror":null},{"id":"https://openalex.org/F4320330802","display_name":"Stan Perron Charitable Foundation","ror":null},{"id":"https://openalex.org/F4320330957","display_name":"Angela Wright Bennett Foundation","ror":null},{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320332359","display_name":"Office of Science","ror":"https://ror.org/00mmn6b08"},{"id":"https://openalex.org/F4320337348","display_name":"National Human Genome Research Institute","ror":"https://ror.org/00baak391"},{"id":"https://openalex.org/F4320337480","display_name":"Basic Energy Sciences","ror":"https://ror.org/05mg91w61"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4387294167.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W1601684588","https://openalex.org/W2108427450","https://openalex.org/W2104328188","https://openalex.org/W648938440","https://openalex.org/W4220795960","https://openalex.org/W2789177613","https://openalex.org/W2396330467","https://openalex.org/W2915108716","https://openalex.org/W1897313079","https://openalex.org/W1517024399"],"abstract_inverted_index":{"Objective:":[0],"Clinical":[1],"deep":[2],"phenotyping":[3,105],"and":[4,106,110,130,132,146,183,226,238],"phenotype":[5,49,107,139],"annotation":[6],"play":[7],"a":[8,48,98],"critical":[9],"role":[10],"in":[11,23,27,45,71,208],"both":[12],"the":[13,28,41,68,72,85,88,101,116,147,166,191,196,199,202,205,213,217,221,223,227,235,241],"diagnosis":[14],"of":[15,74,87,103,115,121,124,143,165,198,220,229,243],"patients":[16],"with":[17,47,156,195],"rare":[18,29],"disorders":[19,30],"as":[20,22,97],"well":[21],"building":[24],"computationally-tractable":[25],"knowledge":[26],"field.":[31],"These":[32],"processes":[33],"rely":[34],"on":[35,180,188],"using":[36,172,234],"ontology":[37],"concepts,":[38],"often":[39],"from":[40],"Human":[42],"Phenotype":[43],"Ontology,":[44],"conjunction":[46],"concept":[50],"recognition":[51],"task":[52],"(supported":[53],"usually":[54],"by":[55],"machine":[56],"learning":[57],"methods)":[58],"to":[59],"curate":[60],"patient":[61],"profiles":[62],"or":[63],"existing":[64],"scientific":[65],"literature.":[66],"With":[67],"significant":[69],"shift":[70],"use":[73,242],"large":[75],"language":[76],"models":[77,94,128,161],"(LLMs)":[78],"for":[79,100,138,247],"most":[80],"NLP":[81],"tasks,":[82],"we":[83],"examine":[84],"performance":[86],"latest":[89],"Generative":[90],"Pre-trained":[91],"Transformer":[92],"(GPT)":[93],"underpinning":[95],"ChatGPT":[96],"foundation":[99],"tasks":[102],"clinical":[104,149,189],"annotation.":[108],"Materials":[109],"Methods:":[111],"The":[112,169],"experimental":[113],"setup":[114],"study":[117],"included":[118],"seven":[119],"prompts":[120],"various":[122],"levels":[123],"specificity,":[125],"two":[126,133],"GPT":[127],"(gpt-3.5-turbo":[129],"gpt-4.0)":[131],"established":[134],"gold":[135],"standard":[136],"corpora":[137],"recognition,":[140],"one":[141],"consisting":[142],"publication":[144,181],"abstracts":[145,182],"other":[148],"observations.":[150],"Results:":[151],"Our":[152],"results":[153,214],"show":[154],"that,":[155],"an":[157],"appropriate":[158],"setup,":[159],"these":[160,244],"can":[162],"achieve":[163],"state":[164,197],"art":[167],"performance.":[168],"best":[170,207],"run,":[171],"few-shot":[173],"learning,":[174],"achieved":[175],"0.58":[176],"macro":[177,185],"F1":[178,186],"score":[179,187],"0.75":[184],"observations,":[190],"former":[192],"being":[193],"comparable":[194],"art,":[200],"while":[201],"latter":[203],"surpassing":[204],"current":[206],"class":[209],"tool.":[210],"Conclusion:":[211],"While":[212],"are":[215],"promising,":[216],"non-deterministic":[218],"nature":[219],"outcomes,":[222],"high":[224],"cost":[225],"lack":[228],"concordance":[230],"between":[231],"different":[232],"runs":[233],"same":[236],"prompt":[237],"input":[239],"make":[240],"LLMs":[245],"challenging":[246],"this":[248],"particular":[249],"task.":[250]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}