{"id":"https://openalex.org/W4416451515","doi":"https://doi.org/10.1016/j.array.2025.100578","title":"Contrastive text embeddings with effective sample mining for enhanced disease diagnosis","display_name":"Contrastive text embeddings with effective sample mining for enhanced disease diagnosis","publication_year":2025,"publication_date":"2025-11-21","ids":{"openalex":"https://openalex.org/W4416451515","doi":"https://doi.org/10.1016/j.array.2025.100578"},"language":"en","primary_location":{"id":"doi:10.1016/j.array.2025.100578","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.array.2025.100578","pdf_url":null,"source":{"id":"https://openalex.org/S4210194039","display_name":"Array","issn_l":"2590-0056","issn":["2590-0056"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Array","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1016/j.array.2025.100578","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5082384515","display_name":"Xuanyi Zhang","orcid":"https://orcid.org/0000-0003-4573-0384"},"institutions":[{"id":"https://openalex.org/I4210134419","display_name":"Neusoft (China)","ror":"https://ror.org/02zc84r97","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210134419"]},{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuanyi Zhang","raw_affiliation_strings":["Neusoft Corporation, Shenyang, 110179, Liaoning, China","School of Computer Science and Engineering, Northeastern University, Shenyang, 110819, Liaoning, China"],"affiliations":[{"raw_affiliation_string":"Neusoft Corporation, Shenyang, 110179, Liaoning, China","institution_ids":["https://openalex.org/I4210134419"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Northeastern University, Shenyang, 110819, Liaoning, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082384515","display_name":"Xuanyi Zhang","orcid":"https://orcid.org/0000-0003-4573-0384"},"institutions":[{"id":"https://openalex.org/I4210134419","display_name":"Neusoft (China)","ror":"https://ror.org/02zc84r97","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210134419"]},{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xuanyi Zhang","raw_affiliation_strings":["Neusoft Corporation, Shenyang, 110179, Liaoning, China","School of Computer Science and Engineering, Northeastern University, Shenyang, 110819, Liaoning, China"],"affiliations":[{"raw_affiliation_string":"Neusoft Corporation, Shenyang, 110179, Liaoning, China","institution_ids":["https://openalex.org/I4210134419"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Northeastern University, Shenyang, 110819, Liaoning, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024674243","display_name":"Genghong Zhao","orcid":"https://orcid.org/0000-0002-7020-862X"},"institutions":[{"id":"https://openalex.org/I4210134419","display_name":"Neusoft (China)","ror":"https://ror.org/02zc84r97","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210134419"]},{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Genghong Zhao","raw_affiliation_strings":["Neusoft Research of Intelligent Healthcare Technology, Co. Ltd, Shenyang, 110167, Liaoning, China","School of Computer Science and Engineering, Northeastern University, Shenyang, 110819, Liaoning, China"],"affiliations":[{"raw_affiliation_string":"Neusoft Research of Intelligent Healthcare Technology, Co. Ltd, Shenyang, 110167, Liaoning, China","institution_ids":["https://openalex.org/I4210134419"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Northeastern University, Shenyang, 110819, Liaoning, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yi Ren","orcid":"https://orcid.org/0009-0007-1713-3239"},"institutions":[{"id":"https://openalex.org/I4210134419","display_name":"Neusoft (China)","ror":"https://ror.org/02zc84r97","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210134419"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Ren","raw_affiliation_strings":["Neusoft Research of Intelligent Healthcare Technology, Co. Ltd, Shenyang, 110167, Liaoning, China"],"affiliations":[{"raw_affiliation_string":"Neusoft Research of Intelligent Healthcare Technology, Co. Ltd, Shenyang, 110167, Liaoning, China","institution_ids":["https://openalex.org/I4210134419"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103890194","display_name":"Weiguang Wang","orcid":"https://orcid.org/0009-0005-3437-6721"},"institutions":[{"id":"https://openalex.org/I4210134419","display_name":"Neusoft (China)","ror":"https://ror.org/02zc84r97","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210134419"]},{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiguang Wang","raw_affiliation_strings":["Neusoft Research of Intelligent Healthcare Technology, Co. Ltd, Shenyang, 110167, Liaoning, China","School of Computer Science and Engineering, Northeastern University, Shenyang, 110819, Liaoning, China"],"affiliations":[{"raw_affiliation_string":"Neusoft Research of Intelligent Healthcare Technology, Co. Ltd, Shenyang, 110167, Liaoning, China","institution_ids":["https://openalex.org/I4210134419"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Northeastern University, Shenyang, 110819, Liaoning, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101192932","display_name":"Yingying Feng","orcid":"https://orcid.org/0009-0004-6701-8739"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingying Feng","raw_affiliation_strings":["School of Computer Science and Engineering, Northeastern University, Shenyang, 110819, Liaoning, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Northeastern University, Shenyang, 110819, Liaoning, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100461935","display_name":"Xia Zhang","orcid":"https://orcid.org/0000-0003-2199-1088"},"institutions":[{"id":"https://openalex.org/I4210134419","display_name":"Neusoft (China)","ror":"https://ror.org/02zc84r97","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210134419"]},{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xia Zhang","raw_affiliation_strings":["Neusoft Corporation, Shenyang, 110179, Liaoning, China","School of Computer Science and Engineering, Northeastern University, Shenyang, 110819, Liaoning, China"],"affiliations":[{"raw_affiliation_string":"Neusoft Corporation, Shenyang, 110179, Liaoning, China","institution_ids":["https://openalex.org/I4210134419"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Northeastern University, Shenyang, 110819, Liaoning, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100461935","display_name":"Xia Zhang","orcid":"https://orcid.org/0000-0003-2199-1088"},"institutions":[{"id":"https://openalex.org/I4210134419","display_name":"Neusoft (China)","ror":"https://ror.org/02zc84r97","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210134419"]},{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xia Zhang","raw_affiliation_strings":["Neusoft Corporation, Shenyang, 110179, Liaoning, China","School of Computer Science and Engineering, Northeastern University, Shenyang, 110819, Liaoning, China"],"affiliations":[{"raw_affiliation_string":"Neusoft Corporation, Shenyang, 110179, Liaoning, China","institution_ids":["https://openalex.org/I4210134419"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Northeastern University, Shenyang, 110819, Liaoning, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038895859","display_name":"J. Y. Liu","orcid":"https://orcid.org/0009-0004-4006-2000"},"institutions":[{"id":"https://openalex.org/I4210134419","display_name":"Neusoft (China)","ror":"https://ror.org/02zc84r97","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210134419"]},{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiren Liu","raw_affiliation_strings":["Neusoft Corporation, Shenyang, 110179, Liaoning, China","School of Computer Science and Engineering, Northeastern University, Shenyang, 110819, Liaoning, China"],"affiliations":[{"raw_affiliation_string":"Neusoft Corporation, Shenyang, 110179, Liaoning, China","institution_ids":["https://openalex.org/I4210134419"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Northeastern University, Shenyang, 110819, Liaoning, China","institution_ids":["https://openalex.org/I9224756"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5038895859","https://openalex.org/A5082384515","https://openalex.org/A5100461935"],"corresponding_institution_ids":["https://openalex.org/I4210134419","https://openalex.org/I9224756"],"apc_list":{"value":1350,"currency":"USD","value_usd":1350},"apc_paid":{"value":1350,"currency":"USD","value_usd":1350},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18475518,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"28","issue":null,"first_page":"100578","last_page":"100578"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.5475999712944031,"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":0.5475999712944031,"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/T10028","display_name":"Topic Modeling","score":0.2685000002384186,"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.026100000366568565,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/medical-diagnosis","display_name":"Medical diagnosis","score":0.6618000268936157},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.6312000155448914},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5083000063896179},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.44429999589920044},{"id":"https://openalex.org/keywords/trace","display_name":"TRACE (psycholinguistics)","score":0.4129999876022339},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.35199999809265137},{"id":"https://openalex.org/keywords/disease","display_name":"Disease","score":0.3483000099658966},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.3188000023365021},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3154999911785126}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7059999704360962},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7002000212669373},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6699000000953674},{"id":"https://openalex.org/C534262118","wikidata":"https://www.wikidata.org/wiki/Q177719","display_name":"Medical diagnosis","level":2,"score":0.6618000268936157},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.6312000155448914},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5083000063896179},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.44429999589920044},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4271000027656555},{"id":"https://openalex.org/C75291252","wikidata":"https://www.wikidata.org/wiki/Q1315756","display_name":"TRACE (psycholinguistics)","level":2,"score":0.4129999876022339},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.35199999809265137},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.3483000099658966},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3188000023365021},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3154999911785126},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.305400013923645},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.30059999227523804},{"id":"https://openalex.org/C2474386","wikidata":"https://www.wikidata.org/wiki/Q461183","display_name":"Text corpus","level":2,"score":0.296099990606308},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2897999882698059},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.2890999913215637},{"id":"https://openalex.org/C2779974597","wikidata":"https://www.wikidata.org/wiki/Q28448986","display_name":"Clinical Practice","level":2,"score":0.2863999903202057},{"id":"https://openalex.org/C3020132585","wikidata":"https://www.wikidata.org/wiki/Q2671652","display_name":"Diagnostic accuracy","level":2,"score":0.2766999900341034},{"id":"https://openalex.org/C2983449737","wikidata":"https://www.wikidata.org/wiki/Q177719","display_name":"Clinical diagnosis","level":2,"score":0.2678000032901764},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.26460000872612},{"id":"https://openalex.org/C96711827","wikidata":"https://www.wikidata.org/wiki/Q17012245","display_name":"Entity linking","level":3,"score":0.26170000433921814},{"id":"https://openalex.org/C63527458","wikidata":"https://www.wikidata.org/wiki/Q5133829","display_name":"Clinical decision support system","level":3,"score":0.25529998540878296},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.2549000084400177},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.25459998846054077},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.25290000438690186}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1016/j.array.2025.100578","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.array.2025.100578","pdf_url":null,"source":{"id":"https://openalex.org/S4210194039","display_name":"Array","issn_l":"2590-0056","issn":["2590-0056"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Array","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:b58338995b264d4cadfc459d7c86bc5f","is_oa":true,"landing_page_url":"https://doaj.org/article/b58338995b264d4cadfc459d7c86bc5f","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Array, Vol 28, Iss , Pp 100578- (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1016/j.array.2025.100578","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.array.2025.100578","pdf_url":null,"source":{"id":"https://openalex.org/S4210194039","display_name":"Array","issn_l":"2590-0056","issn":["2590-0056"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Array","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G172594186","display_name":null,"funder_award_id":"2022YFB2703300","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G5278014143","display_name":null,"funder_award_id":"2023JH26/10100005/04","funder_id":"https://openalex.org/F4320336742","funder_display_name":"Key Research and Development Program of Liaoning Province"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null},{"id":"https://openalex.org/F4320336742","display_name":"Key Research and Development Program of Liaoning Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W2112831187","https://openalex.org/W2900115478","https://openalex.org/W2966312159","https://openalex.org/W2966977115","https://openalex.org/W3006781240","https://openalex.org/W3021792233","https://openalex.org/W3025011581","https://openalex.org/W3025948831","https://openalex.org/W3094217983","https://openalex.org/W3099070320","https://openalex.org/W3101223450","https://openalex.org/W3121644786","https://openalex.org/W3127985875","https://openalex.org/W3134722266","https://openalex.org/W3153990350","https://openalex.org/W3162922479","https://openalex.org/W4229011956","https://openalex.org/W4282960293","https://openalex.org/W4282975369","https://openalex.org/W4297253404","https://openalex.org/W4297347707","https://openalex.org/W4306316957","https://openalex.org/W4312176099","https://openalex.org/W4313439128","https://openalex.org/W4319057838","https://openalex.org/W4319985906","https://openalex.org/W4321229682","https://openalex.org/W4327545654","https://openalex.org/W4360981045","https://openalex.org/W4366835582","https://openalex.org/W4367680667","https://openalex.org/W4380875839","https://openalex.org/W4385574224","https://openalex.org/W4386576685","https://openalex.org/W4387911035","https://openalex.org/W4388615774","https://openalex.org/W4389524338","https://openalex.org/W4389894040","https://openalex.org/W4390739195","https://openalex.org/W4391136507","https://openalex.org/W4392044798","https://openalex.org/W4392193191","https://openalex.org/W4394782456","https://openalex.org/W4400134761","https://openalex.org/W4400190840","https://openalex.org/W4400730982","https://openalex.org/W4401548565","https://openalex.org/W4401834466","https://openalex.org/W4401857375","https://openalex.org/W4401863339","https://openalex.org/W4405822444","https://openalex.org/W4408848940","https://openalex.org/W4409157497","https://openalex.org/W4411147644"],"related_works":[],"abstract_inverted_index":{"Disease":[0,124,220],"diagnosis":[1,52,63,262,281,296,413,456,501],"is":[2,243,286,492],"a":[3,128,205,259,268,388,392,407,415,427,443,475],"pivotal":[4],"task":[5],"in":[6,14,19,175,198,209,291,411,431,496],"Clinical":[7],"Decision":[8],"Support":[9],"(CDS),":[10],"which":[11],"aids":[12],"physicians":[13,73],"differential":[15],"diagnosis,":[16],"faces":[17],"challenges":[18,90],"achieving":[20],"high":[21,408],"precision":[22],"and":[23,42,72,104,138,150,169,185,231,237,312,321,353,366,417],"improving":[24,423],"clinical":[25,106,255,271,446],"adaptability.":[26],"The":[27],"development":[28],"of":[29,57,111,134,204,294,337,363,426,488,499],"deep":[30],"learning":[31,168],"models":[32,64,85,115],"based":[33,126],"on":[34,69,127,234],"pre-trained":[35],"transformers,":[36],"especially":[37],"Large":[38],"Language":[39],"Models":[40],"(LLMs)":[41],"text":[43,113,154,206,428],"embedding":[44,84,114,207,429],"models,":[45,53],"bring":[46],"opportunities":[47],"to":[48,146,200,245,248,257,297,316,344,375,379,400,473,502],"construct":[49,148,258,266,440],"advanced":[50],"disease":[51,62,176,261,280,295,338,412,455,464,500],"but":[54,91],"either":[55],"kind":[56],"model":[58,132,189,208,430],"meets":[59],"challenges.":[60],"LLM-based":[61],"have":[65,460],"not":[66],"performed":[67],"reliability":[68],"generated":[70,81],"diagnoses":[71,484],"difficultly":[74],"trace":[75],"the":[76,88,92,109,162,172,202,223,292,326,335,368,380,398,402,418,424,462,497],"original":[77],"evidence":[78],"for":[79,160,188,279,288,324,454,494],"these":[80],"diagnoses.":[82],"Text":[83],"can":[86],"address":[87],"previous":[89],"domain-specific":[93,163,327],"semantic":[94,164,328,409],"misalignment":[95,165,329],"caused":[96],"by":[97,228],"corpus":[98],"distribution":[99],"differences":[100],"between":[101,414],"open-domain":[102],"corpora":[103],"authentic":[105],"notes":[107],"during":[108,166,213,330,435],"training":[110],"general":[112],"causes":[116],"inaccurate":[117],"ranking.":[118],"In":[119],"this":[120],"paper,":[121],"we":[122,265],"build":[123],"Diagnoser":[125,221],"hybrid":[129],"information":[130,351],"retrieval":[131],"architecture":[133],"an":[135,139,144],"augmented":[136,140],"retriever":[137],"reranker.":[141],"We":[142,194,302,384,439,459],"propose":[143,303],"approach":[145,242],"respectively":[147,233],"DD-retriever":[149],"DD-reranker":[151],"through":[152,349],"contrastive":[153,167,192,214,331,436],"embeddings":[155],"with":[156,274,397,449,468,483],"Effective":[157,179,304],"Sample":[158,180,305],"Mining,":[159],"addressing":[161,325],"thereby":[170,333,422],"enhancing":[171,334],"diagnostic":[173,239],"accuracy":[174,336],"diagnosis.":[177,339],"Specifically,":[178],"Mining":[181,306,342,359],"provides":[182],"high-quality":[183,318,346],"positive":[184,211,310,320,347,381,404,420,433],"negative":[186,314,322,364],"samples":[187,311,323,348,365],"fine-tuning,":[190],"augmenting":[191],"learning.":[193,215,437],"define":[195,385],"Semantic":[196,386],"Target":[197],"order":[199],"improve":[201],"capability":[203,425],"identifying":[210,432],"sample":[212,434],"Extensive":[216],"experiments":[217],"demonstrate":[218],"that":[219,370],"outperforms":[222],"best":[224],"performing":[225],"SOTA":[226],"LLM,":[227],"12.9%,":[229],"22.9%":[230],"24.8%":[232],"top-3,":[235],"top-5":[236],"top-10":[238],"accuracy.":[240],"Our":[241],"validated":[244],"be":[246],"generalized":[247],"any":[249],"hospital,":[250],"using":[251],"its":[252],"private":[253],"annotated":[254,482],"notes,":[256],"specific":[260],"model.":[263],"Additionally,":[264],"PMC-Patients-DD,":[267],"new":[269,444,476],"public":[270,445],"note":[272,447],"dataset":[273,285,448,491],"grounded":[275,450],"truth,":[276,451],"specifically":[277,452],"designed":[278,453],"related":[282,457],"tasks.":[283,458],"This":[284,490],"available":[287,493],"more":[289],"researchers":[290,495],"field":[293,498],"facilitate":[298,503],"further":[299,504],"researches.":[300,505],"\u2022":[301,383,438],"approach,":[307],"mining":[308],"exact":[309,403,419],"hard":[313],"samples,":[315],"provide":[317],"medical":[319],"learning,":[332],"Exact":[340],"Positive":[341],"aims":[343],"mine":[345,401],"LLM\u2019s":[350],"extraction":[352],"web":[354],"search,":[355],"while":[356],"Hard":[357],"Negative":[358],"randomly":[360],"generates":[361],"numbers":[362],"selects":[367],"ones":[369],"are":[371],"neither":[372],"completely":[373],"irrelevant":[374],"nor":[376],"highly":[377],"semantically-related":[378],"samples.":[382],"Target,":[387],"vector":[389],"extracted":[390],"from":[391,466],"query":[393,399,416],"or":[394],"explicitly":[395],"associated":[396],"sample,":[405,421],"establishing":[406],"correlation":[410],"PMC-Patients-DD":[441],"dataset,":[442,477],"integrated":[461],"mined":[463],"names":[465],"PMC-Patients":[467],"their":[469],"corresponding":[470],"patient":[471,480],"summaries":[472,481],"create":[474],"including":[478],"29470":[479],"covering":[485],"1145":[486],"types":[487],"diseases.":[489]},"counts_by_year":[],"updated_date":"2026-04-20T07:46:08.049788","created_date":"2025-11-23T00:00:00"}
