{"id":"https://openalex.org/W3183592968","doi":"https://doi.org/10.1186/s12911-021-01459-0","title":"Transformers-sklearn: a toolkit for medical language understanding with transformer-based models","display_name":"Transformers-sklearn: a toolkit for medical language understanding with transformer-based models","publication_year":2021,"publication_date":"2021-07-01","ids":{"openalex":"https://openalex.org/W3183592968","doi":"https://doi.org/10.1186/s12911-021-01459-0","mag":"3183592968","pmid":"https://pubmed.ncbi.nlm.nih.gov/34330244"},"language":"en","primary_location":{"id":"doi:10.1186/s12911-021-01459-0","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12911-021-01459-0","pdf_url":"https://bmcmedinformdecismak.biomedcentral.com/track/pdf/10.1186/s12911-021-01459-0","source":{"id":"https://openalex.org/S107516304","display_name":"BMC Medical Informatics and Decision Making","issn_l":"1472-6947","issn":["1472-6947"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Medical Informatics and Decision Making","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://bmcmedinformdecismak.biomedcentral.com/track/pdf/10.1186/s12911-021-01459-0","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5035355520","display_name":"Feihong Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I200296433","display_name":"Chinese Academy of Medical Sciences & Peking Union Medical College","ror":"https://ror.org/02drdmm93","country_code":"CN","type":"education","lineage":["https://openalex.org/I200296433"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Feihong Yang","raw_affiliation_strings":["Institute of Medical Information and Library, Chinese Academy of Medical Sciences/Peking Union Medical College, 3rd Yabao Road, Beijing, 100020, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Medical Information and Library, Chinese Academy of Medical Sciences/Peking Union Medical College, 3rd Yabao Road, Beijing, 100020, China","institution_ids":["https://openalex.org/I200296433"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054657033","display_name":"Xuwen Wang","orcid":"https://orcid.org/0000-0003-3022-6513"},"institutions":[{"id":"https://openalex.org/I200296433","display_name":"Chinese Academy of Medical Sciences & Peking Union Medical College","ror":"https://ror.org/02drdmm93","country_code":"CN","type":"education","lineage":["https://openalex.org/I200296433"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuwen Wang","raw_affiliation_strings":["Institute of Medical Information and Library, Chinese Academy of Medical Sciences/Peking Union Medical College, 3rd Yabao Road, Beijing, 100020, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Medical Information and Library, Chinese Academy of Medical Sciences/Peking Union Medical College, 3rd Yabao Road, Beijing, 100020, China","institution_ids":["https://openalex.org/I200296433"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042232909","display_name":"Hetong Ma","orcid":"https://orcid.org/0000-0003-0040-2846"},"institutions":[{"id":"https://openalex.org/I200296433","display_name":"Chinese Academy of Medical Sciences & Peking Union Medical College","ror":"https://ror.org/02drdmm93","country_code":"CN","type":"education","lineage":["https://openalex.org/I200296433"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hetong Ma","raw_affiliation_strings":["Institute of Medical Information and Library, Chinese Academy of Medical Sciences/Peking Union Medical College, 3rd Yabao Road, Beijing, 100020, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Medical Information and Library, Chinese Academy of Medical Sciences/Peking Union Medical College, 3rd Yabao Road, Beijing, 100020, China","institution_ids":["https://openalex.org/I200296433"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074284592","display_name":"Jiao Li","orcid":"https://orcid.org/0000-0001-6391-8343"},"institutions":[{"id":"https://openalex.org/I200296433","display_name":"Chinese Academy of Medical Sciences & Peking Union Medical College","ror":"https://ror.org/02drdmm93","country_code":"CN","type":"education","lineage":["https://openalex.org/I200296433"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiao Li","raw_affiliation_strings":["Institute of Medical Information and Library, Chinese Academy of Medical Sciences/Peking Union Medical College, 3rd Yabao Road, Beijing, 100020, China. li.jiao@imicams.ac.cn","Institute of Medical Information and Library, Chinese Academy of Medical Sciences/Peking Union Medical College, 3rd Yabao Road, Beijing, 100020, China"],"raw_orcid":"https://orcid.org/0000-0001-6391-8343","affiliations":[{"raw_affiliation_string":"Institute of Medical Information and Library, Chinese Academy of Medical Sciences/Peking Union Medical College, 3rd Yabao Road, Beijing, 100020, China. li.jiao@imicams.ac.cn","institution_ids":["https://openalex.org/I200296433"]},{"raw_affiliation_string":"Institute of Medical Information and Library, Chinese Academy of Medical Sciences/Peking Union Medical College, 3rd Yabao Road, Beijing, 100020, China","institution_ids":["https://openalex.org/I200296433"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5035355520"],"corresponding_institution_ids":["https://openalex.org/I200296433"],"apc_list":{"value":1570,"currency":"GBP","value_usd":1925},"apc_paid":{"value":1570,"currency":"GBP","value_usd":1925},"fwci":4.198,"has_fulltext":true,"cited_by_count":42,"citation_normalized_percentile":{"value":0.95012375,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"21","issue":"S2","first_page":"90","last_page":"90"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.42739999294281006,"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":0.42739999294281006,"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":0.20479999482631683,"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":0.07180000096559525,"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/computer-science","display_name":"Computer science","score":0.7873055338859558},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.7138601541519165},{"id":"https://openalex.org/keywords/python","display_name":"Python (programming language)","score":0.7021831274032593},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.5479311347007751},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49912118911743164},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.49568426609039307},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33252161741256714},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.20457598567008972},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10076436400413513}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7873055338859558},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.7138601541519165},{"id":"https://openalex.org/C519991488","wikidata":"https://www.wikidata.org/wiki/Q28865","display_name":"Python (programming language)","level":2,"score":0.7021831274032593},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.5479311347007751},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49912118911743164},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.49568426609039307},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33252161741256714},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.20457598567008972},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10076436400413513},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007802","descriptor_name":"Language","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007802","descriptor_name":"Language","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007802","descriptor_name":"Language","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D009323","descriptor_name":"Natural Language Processing","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D009323","descriptor_name":"Natural Language Processing","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D009323","descriptor_name":"Natural Language Processing","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D019303","descriptor_name":"Multilingualism","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D019303","descriptor_name":"Multilingualism","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D019303","descriptor_name":"Multilingualism","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":4,"locations":[{"id":"doi:10.1186/s12911-021-01459-0","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12911-021-01459-0","pdf_url":"https://bmcmedinformdecismak.biomedcentral.com/track/pdf/10.1186/s12911-021-01459-0","source":{"id":"https://openalex.org/S107516304","display_name":"BMC Medical Informatics and Decision Making","issn_l":"1472-6947","issn":["1472-6947"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Medical Informatics and Decision Making","raw_type":"journal-article"},{"id":"pmid:34330244","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34330244","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_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":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC medical informatics and decision making","raw_type":null},{"id":"pmh:oai:doaj.org/article:4e83dda288a44e439317a93da90d971b","is_oa":true,"landing_page_url":"https://doaj.org/article/4e83dda288a44e439317a93da90d971b","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"BMC Medical Informatics and Decision Making, Vol 21, Iss S2, Pp 1-8 (2021)","raw_type":"article"},{"id":"pmh:oai:pubmedcentral.nih.gov:8323195","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8323195","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":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":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"BMC Med Inform Decis Mak","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1186/s12911-021-01459-0","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12911-021-01459-0","pdf_url":"https://bmcmedinformdecismak.biomedcentral.com/track/pdf/10.1186/s12911-021-01459-0","source":{"id":"https://openalex.org/S107516304","display_name":"BMC Medical Informatics and Decision Making","issn_l":"1472-6947","issn":["1472-6947"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Medical Informatics and Decision Making","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Quality Education","score":0.8100000023841858,"id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G279875680","display_name":null,"funder_award_id":"61906214","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6202994627","display_name":null,"funder_award_id":"Z200016","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6839918318","display_name":null,"funder_award_id":"2018-I2M-AI-016","funder_id":"https://openalex.org/F4320323137","funder_display_name":"Chinese Academy of Medical Sciences"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320323137","display_name":"Chinese Academy of Medical Sciences","ror":"https://ror.org/03cve4549"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3183592968.pdf","grobid_xml":"https://content.openalex.org/works/W3183592968.grobid-xml"},"referenced_works_count":20,"referenced_works":["https://openalex.org/W2521200999","https://openalex.org/W2586665457","https://openalex.org/W2626778328","https://openalex.org/W2735784619","https://openalex.org/W2880875857","https://openalex.org/W2914120296","https://openalex.org/W2950511172","https://openalex.org/W2950813464","https://openalex.org/W2963341956","https://openalex.org/W2963691697","https://openalex.org/W2965373594","https://openalex.org/W2970390493","https://openalex.org/W2970597249","https://openalex.org/W2974580236","https://openalex.org/W2978017171","https://openalex.org/W2979826702","https://openalex.org/W2980282514","https://openalex.org/W2996428491","https://openalex.org/W4285719527","https://openalex.org/W6675354045"],"related_works":["https://openalex.org/W4288365749","https://openalex.org/W2936497627","https://openalex.org/W3013624417","https://openalex.org/W4287826556","https://openalex.org/W3098382480","https://openalex.org/W4287598411","https://openalex.org/W3094871513","https://openalex.org/W3100913109","https://openalex.org/W3198458223","https://openalex.org/W3126642501"],"abstract_inverted_index":{"BACKGROUND:":[0],"Transformer":[1],"is":[2,138,168,247,251,297],"an":[3,42],"attention-based":[4],"architecture":[5],"proven":[6],"the":[7,17,31,34,52,67,70,86,91,100,115,121,124,131,134,174,182,235,240,253,280,293,300,317,345],"state-of-the-art":[8],"model":[9,185],"in":[10,25,37,56,192],"natural":[11],"language":[12,27,200,313,337],"processing":[13],"(NLP).":[14],"To":[15],"reduce":[16],"difficulty":[18],"of":[19,33,54,69,123,133,244,255,273,290,302,326,347],"beginning":[20],"to":[21,44,180,343],"use":[22],"transformer-based":[23,112],"models":[24,113,268],"medical":[26,199,206,237,312,336],"understanding":[28,314,338],"and":[29,63,72,97,127,152,159,187,226,276,283,286,324],"expand":[30],"capability":[32],"scikit-learn":[35,73,318],"toolkit":[36,47,141,307],"deep":[38],"learning,":[39],"we":[40],"proposed":[41,306],"easy":[43],"learn":[45],"Python":[46,79],"named":[48,92],"transformers-sklearn.":[49,193],"By":[50],"wrapping":[51],"interfaces":[53],"transformers":[55,71],"only":[57,178],"three":[58,78,106],"functions":[59],"(i.e.,":[60],"fit,":[61],"score,":[62],"predict),":[64],"transformers-sklearn":[65,137,172,263,327],"combines":[66],"advantages":[68],"toolkits.":[74],"METHODS:":[75],"In":[76,234,333],"transformers-sklearn,":[77],"classes":[80],"were":[81],"implemented,":[82],"namely,":[83],"BERTologyClassifier":[84],"for":[85,90,99,110,119,129,204,213,221,228],"classification":[87],"task,":[88,96,295],"BERTologyNERClassifier":[89],"entity":[93,218,224],"recognition":[94,225],"(NER)":[95],"BERTologyRegressor":[98],"regression":[101],"task.":[102],"Each":[103],"class":[104],"contains":[105],"methods,":[107],"i.e.,":[108],"fit":[109],"fine-tuning":[111],"with":[114,173,299],"training":[116,188],"dataset,":[117],"score":[118],"evaluating":[120],"performance":[122],"fine-tuned":[125],"model,":[126],"predict":[128],"predicting":[130],"labels":[132],"test":[135],"dataset.":[136,183],"a":[139,147,287],"user-friendly":[140],"that":[142,262],"(1)":[143],"Is":[144],"customizable":[145],"via":[146],"few":[148],"parameters":[149],"(e.g.,":[150],"model_name_or_path":[151],"model_type),":[153],"(2)":[154],"Supports":[155],"multilingual":[156],"NLP":[157,238],"tasks,":[158,239],"(3)":[160],"Requires":[161],"less":[162],"coding.":[163],"The":[164,184,258,305,322],"input":[165],"data":[166],"format":[167],"automatically":[169],"generated":[170],"by":[171],"annotated":[175],"corpus.":[176],"Newcomers":[177],"need":[179],"prepare":[181],"framework":[186],"methods":[189],"are":[190,328],"predefined":[191],"RESULTS:":[194],"We":[195],"collected":[196],"four":[197,236],"open-source":[198],"datasets,":[201],"including":[202],"TrialClassification":[203],"Chinese":[205,222],"trial":[207],"text":[208,216],"multi":[209],"label":[210],"classification,":[211],"BC5CDR":[212,282],"English":[214,229],"biomedical":[215,230],"name":[217],"recognition,":[219],"DiabetesNER":[220,284],"diabetes":[223],"BIOSSES":[227,294],"sentence":[231],"similarity":[232],"estimation.":[233],"average":[241],"code":[242,323],"size":[243,254],"our":[245],"script":[246],"45":[248],"lines/task,":[249],"which":[250,296],"one-sixth":[252],"transformers'":[256],"script.":[257],"experimental":[259],"results":[260,301],"show":[261],"based":[264],"on":[265,279,292],"pretrained":[266],"BERT":[267],"achieved":[269],"macro":[270],"F1":[271],"scores":[272],"0.8225,":[274],"0.8703":[275],"0.6908,":[277],"respectively,":[278],"TrialClassification,":[281],"tasks":[285,315,339],"Pearson":[288],"correlation":[289],"0.8260":[291],"consistent":[298],"transformers.":[303],"CONCLUSIONS:":[304],"could":[308],"help":[309],"newcomers":[310],"address":[311],"using":[316],"coding":[319],"style":[320],"easily.":[321],"tutorials":[325],"available":[329],"at":[330],"https://doi.org/10.5281/zenodo.4453803":[331],".":[332],"future,":[334],"more":[335],"will":[340],"be":[341],"supported":[342],"improve":[344],"applications":[346],"transformers_sklearn.":[348]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":13},{"year":2022,"cited_by_count":9}],"updated_date":"2026-05-12T08:28:47.272897","created_date":"2025-10-10T00:00:00"}