{"id":"https://openalex.org/W4399353257","doi":"https://doi.org/10.1016/j.artmed.2024.102904","title":"Pre-trained language models in medicine: A survey","display_name":"Pre-trained language models in medicine: A survey","publication_year":2024,"publication_date":"2024-06-05","ids":{"openalex":"https://openalex.org/W4399353257","doi":"https://doi.org/10.1016/j.artmed.2024.102904","pmid":"https://pubmed.ncbi.nlm.nih.gov/38917600"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.artmed.2024.102904","pdf_url":null,"source":{"id":"https://openalex.org/S42468263","display_name":"Artificial Intelligence in Medicine","issn_l":"0933-3657","issn":["0933-3657","1873-2860"],"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":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},"type":"review","type_crossref":"journal-article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1016/j.artmed.2024.102904","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5030600444","display_name":"Xudong Luo","orcid":"https://orcid.org/0000-0001-6940-9531"},"institutions":[{"id":"https://openalex.org/I29739308","display_name":"Guangxi Normal University","ror":"https://ror.org/02frt9q65","country_code":"CN","type":"education","lineage":["https://openalex.org/I29739308"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xudong Luo","raw_affiliation_strings":["Guangxi Key Lab of Multi-source Information Mining, Guangxi Normal University, Guilin 541004, China","Key Laboratory of Education Blockchain and Intelligent Technology, Ministry of Education, Guangxi Normal University, Guilin 541004, China","School of Computer Science and Engineering, Guangxi Normal University, Guilin 541004, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Guangxi Normal University, Guilin 541004, China","institution_ids":["https://openalex.org/I29739308"]},{"raw_affiliation_string":"Key Laboratory of Education Blockchain and Intelligent Technology, Ministry of Education, Guangxi Normal University, Guilin 541004, China","institution_ids":["https://openalex.org/I29739308"]},{"raw_affiliation_string":"Guangxi Key Lab of Multi-source Information Mining, Guangxi Normal University, Guilin 541004, China","institution_ids":["https://openalex.org/I29739308"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067020539","display_name":"Zhiqi Deng","orcid":null},"institutions":[{"id":"https://openalex.org/I29739308","display_name":"Guangxi Normal University","ror":"https://ror.org/02frt9q65","country_code":"CN","type":"education","lineage":["https://openalex.org/I29739308"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiqi Deng","raw_affiliation_strings":["Guangxi Key Lab of Multi-source Information Mining, Guangxi Normal University, Guilin 541004, China","Key Laboratory of Education Blockchain and Intelligent Technology, Ministry of Education, Guangxi Normal University, Guilin 541004, China","School of Computer Science and Engineering, Guangxi Normal University, Guilin 541004, China"],"affiliations":[{"raw_affiliation_string":"Guangxi Key Lab of Multi-source Information Mining, Guangxi Normal University, Guilin 541004, China","institution_ids":["https://openalex.org/I29739308"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Guangxi Normal University, Guilin 541004, China","institution_ids":["https://openalex.org/I29739308"]},{"raw_affiliation_string":"Key Laboratory of Education Blockchain and Intelligent Technology, Ministry of Education, Guangxi Normal University, Guilin 541004, China","institution_ids":["https://openalex.org/I29739308"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113054351","display_name":"Binxia Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I29739308","display_name":"Guangxi Normal University","ror":"https://ror.org/02frt9q65","country_code":"CN","type":"education","lineage":["https://openalex.org/I29739308"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Binxia Yang","raw_affiliation_strings":["Guangxi Key Lab of Multi-source Information Mining, Guangxi Normal University, Guilin 541004, China","Key Laboratory of Education Blockchain and Intelligent Technology, Ministry of Education, Guangxi Normal University, Guilin 541004, China","School of Computer Science and Engineering, Guangxi Normal University, Guilin 541004, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Education Blockchain and Intelligent Technology, Ministry of Education, Guangxi Normal University, Guilin 541004, China","institution_ids":["https://openalex.org/I29739308"]},{"raw_affiliation_string":"Guangxi Key Lab of Multi-source Information Mining, Guangxi Normal University, Guilin 541004, China","institution_ids":["https://openalex.org/I29739308"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Guangxi Normal University, Guilin 541004, China","institution_ids":["https://openalex.org/I29739308"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038336825","display_name":"Michael Y. Luo","orcid":null},"institutions":[{"id":"https://openalex.org/I241749","display_name":"University of Cambridge","ror":"https://ror.org/013meh722","country_code":"GB","type":"education","lineage":["https://openalex.org/I241749"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Michael Y. Luo","raw_affiliation_strings":["Emmanuel College, Cambridge University, Cambridge, CB2 3AP, UK"],"affiliations":[{"raw_affiliation_string":"Emmanuel College, Cambridge University, Cambridge, CB2 3AP, UK","institution_ids":["https://openalex.org/I241749"]}]}],"institution_assertions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5030600444"],"corresponding_institution_ids":["https://openalex.org/I29739308"],"apc_list":{"value":3230,"currency":"USD","value_usd":3230,"provenance":"doaj"},"apc_paid":{"value":3230,"currency":"USD","value_usd":3230,"provenance":"doaj"},"fwci":2.405,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.701266,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"154","issue":null,"first_page":"102904","last_page":"102904"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9984,"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/T10028","display_name":"Topic Modeling","score":0.9984,"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":0.9957,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.9844,"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/sentiment-analysis","display_name":"Sentiment Analysis","score":0.49402052}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8207439},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.61949193},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6046151},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5206291},{"id":"https://openalex.org/C2778805511","wikidata":"https://www.wikidata.org/wiki/Q1713","display_name":"Citation","level":2,"score":0.51808333},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.49402052},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.4840502},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.4837625},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46121418},{"id":"https://openalex.org/C203005215","wikidata":"https://www.wikidata.org/wiki/Q79798","display_name":"Machine translation","level":2,"score":0.44764328},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.38450062},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.1779117},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[{"descriptor_ui":"D057225","descriptor_name":"Data Mining","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":"","qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":"","qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D009323","descriptor_name":"Natural Language Processing","qualifier_ui":"","qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D011795","descriptor_name":"Surveys and Questionnaires","qualifier_ui":"","qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.artmed.2024.102904","pdf_url":null,"source":{"id":"https://openalex.org/S42468263","display_name":"Artificial Intelligence in Medicine","issn_l":"0933-3657","issn":["0933-3657","1873-2860"],"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":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},{"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/38917600","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":["National Institutes of Health"],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.artmed.2024.102904","pdf_url":null,"source":{"id":"https://openalex.org/S42468263","display_name":"Artificial Intelligence in Medicine","issn_l":"0933-3657","issn":["0933-3657","1873-2860"],"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":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},"sustainable_development_goals":[{"display_name":"Quality education","id":"https://metadata.un.org/sdg/4","score":0.77}],"grants":[{"funder":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China","award_id":"62162054"}],"datasets":[],"versions":[],"referenced_works_count":125,"referenced_works":["https://openalex.org/W1005454186","https://openalex.org/W1507711477","https://openalex.org/W1556721226","https://openalex.org/W181040134","https://openalex.org/W1884099301","https://openalex.org/W1956340063","https://openalex.org/W1966812932","https://openalex.org/W1973968558","https://openalex.org/W1975879668","https://openalex.org/W1981208470","https://openalex.org/W2002514548","https://openalex.org/W2013469333","https://openalex.org/W2039182738","https://openalex.org/W2039240409","https://openalex.org/W2071879021","https://openalex.org/W2093805119","https://openalex.org/W2100627415","https://openalex.org/W2101105183","https://openalex.org/W2116446440","https://openalex.org/W2143205289","https://openalex.org/W2145870108","https://openalex.org/W2152772232","https://openalex.org/W2154142897","https://openalex.org/W2168041406","https://openalex.org/W2169099542","https://openalex.org/W2278131208","https://openalex.org/W2332528840","https://openalex.org/W2341078838","https://openalex.org/W2345195116","https://openalex.org/W2346452181","https://openalex.org/W2396881363","https://openalex.org/W2594492513","https://openalex.org/W2604410201","https://openalex.org/W2735580341","https://openalex.org/W2766458820","https://openalex.org/W2789244308","https://openalex.org/W2807470877","https://openalex.org/W2887382745","https://openalex.org/W2888120268","https://openalex.org/W2888967035","https://openalex.org/W2889272240","https://openalex.org/W2891772212","https://openalex.org/W2896457183","https://openalex.org/W2904008843","https://openalex.org/W2908840510","https://openalex.org/W2911489562","https://openalex.org/W2915824643","https://openalex.org/W2923014074","https://openalex.org/W2936695845","https://openalex.org/W2937845937","https://openalex.org/W2962739339","https://openalex.org/W2962809918","https://openalex.org/W2963323070","https://openalex.org/W2963748441","https://openalex.org/W2965373594","https://openalex.org/W2970232715","https://openalex.org/W2970482702","https://openalex.org/W2977683229","https://openalex.org/W2979250794","https://openalex.org/W2995225687","https://openalex.org/W2997204042","https://openalex.org/W2999309192","https://openalex.org/W3011594683","https://openalex.org/W3015453090","https://openalex.org/W3020786614","https://openalex.org/W3023360076","https://openalex.org/W3033544963","https://openalex.org/W3045332379","https://openalex.org/W3045801920","https://openalex.org/W3081304278","https://openalex.org/W3088335873","https://openalex.org/W3095319910","https://openalex.org/W3102251128","https://openalex.org/W3105214104","https://openalex.org/W3106219395","https://openalex.org/W3113541070","https://openalex.org/W3114632476","https://openalex.org/W3131765384","https://openalex.org/W3146463158","https://openalex.org/W3146718238","https://openalex.org/W3146994407","https://openalex.org/W3152494620","https://openalex.org/W3152503596","https://openalex.org/W3169341408","https://openalex.org/W3169483174","https://openalex.org/W3174995573","https://openalex.org/W3175423875","https://openalex.org/W3175533348","https://openalex.org/W3178751578","https://openalex.org/W3184140580","https://openalex.org/W3206730738","https://openalex.org/W3215490307","https://openalex.org/W378747138","https://openalex.org/W4205403018","https://openalex.org/W4206537918","https://openalex.org/W4210721047","https://openalex.org/W4210827551","https://openalex.org/W4223547049","https://openalex.org/W4230292813","https://openalex.org/W4285807172","https://openalex.org/W4287867774","https://openalex.org/W4288089799","https://openalex.org/W4292199287","https://openalex.org/W4294763143","https://openalex.org/W4297687090","https://openalex.org/W4319304435","https://openalex.org/W4319460874","https://openalex.org/W4319662928","https://openalex.org/W4322761615","https://openalex.org/W4324135233","https://openalex.org/W4365512576","https://openalex.org/W4367858557","https://openalex.org/W4380302056","https://openalex.org/W4380715596","https://openalex.org/W4382246105","https://openalex.org/W4383618720","https://openalex.org/W4384561707","https://openalex.org/W4385245566","https://openalex.org/W4385571629","https://openalex.org/W4385572244","https://openalex.org/W4385573478","https://openalex.org/W4385822273","https://openalex.org/W4387500346","https://openalex.org/W4393300262","https://openalex.org/W80463681"],"related_works":["https://openalex.org/W4386247111","https://openalex.org/W4327642362","https://openalex.org/W3107474891","https://openalex.org/W3089396779","https://openalex.org/W3013279174","https://openalex.org/W2775554247","https://openalex.org/W2587014613","https://openalex.org/W2548633793","https://openalex.org/W2250213760","https://openalex.org/W2110168585"],"abstract_inverted_index":{"With":[0],"the":[1,31,49,60,98,101,104,109,116,123,154,159,167,171,175,180,194,217,238],"rapid":[2],"progress":[3],"in":[4,23,34,53,64,162,221,250],"Natural":[5],"Language":[6,10],"Processing":[7],"(NLP),":[8],"Pre-trained":[9],"Models":[11],"(PLM)":[12],"such":[13],"as":[14],"BERT,":[15],"BioBERT,":[16],"and":[17,47,58,84,120,122,147,156,174,177,182,213,237,252,260],"ChatGPT":[18],"have":[19],"shown":[20],"great":[21],"potential":[22,149],"various":[24,38],"medical":[25,39,65,80,253],"NLP":[26,40,248],"tasks.":[27,41],"This":[28],"paper":[29,164],"surveys":[30],"cutting-edge":[32],"achievements":[33],"applying":[35,107,113,247],"PLMs":[36,52,114,220],"to":[37,204,215,256],"Specifically,":[42],"we":[43,56,92,152,191,201],"first":[44,93],"brief":[45],"PLMS":[46],"outline":[48],"research":[50,134,160,197,206],"of":[51,62,90,97,106,112,131,158,170,179,219,233],"medicine.":[54],"Next,":[55],"categorise":[57],"discuss":[59],"types":[61],"tasks":[63],"NLP,":[66],"covering":[67],"text":[68,85],"summarisation,":[69],"question-answering,":[70],"machine":[71],"translation,":[72],"sentiment":[73],"analysis,":[74],"named":[75],"entity":[76],"recognition,":[77],"information":[78],"extraction,":[79,83],"education,":[81],"relation":[82],"mining.":[86],"For":[87],"each":[88],"type":[89],"task,":[91],"provide":[94],"an":[95],"overview":[96],"basic":[99,110],"concepts,":[100],"main":[102],"methodologies,":[103],"advantages":[105],"PLMs,":[108],"steps":[111],"application,":[115],"datasets":[117],"for":[118,125,245],"training":[119],"testing,":[121],"metrics":[124],"task":[126],"evaluation.":[127],"Subsequently,":[128],"a":[129],"summary":[130],"recent":[132],"important":[133],"findings":[135],"is":[136],"presented,":[137],"analysing":[138],"their":[139,258],"motivations,":[140],"strengths":[141],"vs":[142,145],"weaknesses,":[143],"similarities":[144],"differences,":[146],"discussing":[148],"limitations.":[150],"Also,":[151],"assess":[153],"quality":[155],"influence":[157],"reviewed":[161,173],"this":[163,226],"by":[165],"comparing":[166],"citation":[168],"count":[169],"papers":[172],"reputation":[176],"impact":[178],"conferences":[181],"journals":[183],"where":[184],"they":[185],"are":[186,242],"published.":[187],"Through":[188],"these":[189],"indicators,":[190],"further":[192],"identify":[193],"most":[195],"concerned":[196],"topics":[198],"currently.":[199],"Finally,":[200],"look":[202],"forward":[203],"future":[205],"directions,":[207],"including":[208],"enhancing":[209],"models'":[210],"reliability,":[211],"explainability,":[212],"fairness,":[214],"promote":[216],"application":[218],"clinical":[222],"practice.":[223],"In":[224],"addition,":[225],"survey":[227],"also":[228],"collect":[229],"some":[230,234],"download":[231],"links":[232],"model":[235],"codes":[236],"relevant":[239],"datasets,":[240],"which":[241],"valuable":[243],"references":[244],"researchers":[246],"techniques":[249],"medicine":[251],"professionals":[254],"seeking":[255],"enhance":[257],"expertise":[259],"healthcare":[261],"service":[262],"through":[263],"AI":[264],"technology.":[265]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4399353257","counts_by_year":[{"year":2024,"cited_by_count":3}],"updated_date":"2025-01-20T23:55:11.562616","created_date":"2024-06-06"}