{"id":"https://openalex.org/W4399889932","doi":"https://doi.org/10.1093/jamia/ocae147","title":"LEAP: LLM instruction-example adaptive prompting framework for biomedical relation extraction","display_name":"LEAP: LLM instruction-example adaptive prompting framework for biomedical relation extraction","publication_year":2024,"publication_date":"2024-06-03","ids":{"openalex":"https://openalex.org/W4399889932","doi":"https://doi.org/10.1093/jamia/ocae147","pmid":"https://pubmed.ncbi.nlm.nih.gov/38904416"},"language":"en","primary_location":{"id":"doi:10.1093/jamia/ocae147","is_oa":false,"landing_page_url":"https://doi.org/10.1093/jamia/ocae147","pdf_url":null,"source":{"id":"https://openalex.org/S129839026","display_name":"Journal of the American Medical Informatics Association","issn_l":"1067-5027","issn":["1067-5027","1527-974X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the American Medical Informatics Association","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11339510/pdf/ocae147.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5026404757","display_name":"Huixue Zhou","orcid":"https://orcid.org/0000-0002-6524-5506"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Huixue Zhou","raw_affiliation_strings":["Institute for Health Informatics, University of Minnesota, Minneapolis, MN 55455, United States"],"raw_orcid":"https://orcid.org/0000-0002-6524-5506","affiliations":[{"raw_affiliation_string":"Institute for Health Informatics, University of Minnesota, Minneapolis, MN 55455, United States","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101907703","display_name":"Mingchen Li","orcid":"https://orcid.org/0000-0001-5181-8193"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mingchen Li","raw_affiliation_strings":["Division of Computational Health Sciences, Department of Surgery, University of Minnesota, Minneapolis, MN 55455, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Division of Computational Health Sciences, Department of Surgery, University of Minnesota, Minneapolis, MN 55455, United States","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034370661","display_name":"Yongkang Xiao","orcid":"https://orcid.org/0000-0002-8808-8371"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yongkang Xiao","raw_affiliation_strings":["Institute for Health Informatics, University of Minnesota, Minneapolis, MN 55455, United States"],"raw_orcid":"https://orcid.org/0000-0002-8808-8371","affiliations":[{"raw_affiliation_string":"Institute for Health Informatics, University of Minnesota, Minneapolis, MN 55455, United States","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101605012","display_name":"Han Yang","orcid":"https://orcid.org/0009-0000-4322-6753"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Han Yang","raw_affiliation_strings":["Institute for Health Informatics, University of Minnesota, Minneapolis, MN 55455, United States"],"raw_orcid":"https://orcid.org/0009-0000-4322-6753","affiliations":[{"raw_affiliation_string":"Institute for Health Informatics, University of Minnesota, Minneapolis, MN 55455, United States","institution_ids":["https://openalex.org/I130238516"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100421963","display_name":"Rui Zhang","orcid":"https://orcid.org/0000-0001-8258-3585"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Rui Zhang","raw_affiliation_strings":["Division of Computational Health Sciences, Department of Surgery, University of Minnesota, Minneapolis, MN 55455, United States"],"raw_orcid":"https://orcid.org/0000-0001-8258-3585","affiliations":[{"raw_affiliation_string":"Division of Computational Health Sciences, Department of Surgery, University of Minnesota, Minneapolis, MN 55455, United States","institution_ids":["https://openalex.org/I130238516"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5100421963"],"corresponding_institution_ids":["https://openalex.org/I130238516"],"apc_list":{"value":4549,"currency":"USD","value_usd":4549},"apc_paid":null,"fwci":6.4637,"has_fulltext":true,"cited_by_count":28,"citation_normalized_percentile":{"value":0.97024495,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"31","issue":"9","first_page":"2010","last_page":"2018"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.3901999890804291,"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":0.3901999890804291,"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":0.21170000731945038,"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":0.06400000303983688,"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/computer-science","display_name":"Computer science","score":0.7832518815994263},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5714784264564514},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5451090931892395},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.49172475934028625},{"id":"https://openalex.org/keywords/relationship-extraction","display_name":"Relationship extraction","score":0.44812506437301636},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4056650996208191},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35776910185813904},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.24851247668266296},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07364937663078308},{"id":"https://openalex.org/keywords/systems-engineering","display_name":"Systems engineering","score":0.06187474727630615}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7832518815994263},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5714784264564514},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5451090931892395},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.49172475934028625},{"id":"https://openalex.org/C153604712","wikidata":"https://www.wikidata.org/wiki/Q7310755","display_name":"Relationship extraction","level":3,"score":0.44812506437301636},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4056650996208191},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35776910185813904},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.24851247668266296},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07364937663078308},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.06187474727630615},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[{"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":"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":"D009323","descriptor_name":"Natural Language Processing","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D057225","descriptor_name":"Data Mining","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D057225","descriptor_name":"Data Mining","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D057225","descriptor_name":"Data Mining","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D057225","descriptor_name":"Data Mining","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D057225","descriptor_name":"Data Mining","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D057225","descriptor_name":"Data Mining","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D057225","descriptor_name":"Data Mining","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D066264","descriptor_name":"Datasets as Topic","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D066264","descriptor_name":"Datasets as Topic","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D066264","descriptor_name":"Datasets as Topic","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D066264","descriptor_name":"Datasets as Topic","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D066264","descriptor_name":"Datasets as Topic","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D066264","descriptor_name":"Datasets as Topic","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D066264","descriptor_name":"Datasets as Topic","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":3,"locations":[{"id":"doi:10.1093/jamia/ocae147","is_oa":false,"landing_page_url":"https://doi.org/10.1093/jamia/ocae147","pdf_url":null,"source":{"id":"https://openalex.org/S129839026","display_name":"Journal of the American Medical Informatics Association","issn_l":"1067-5027","issn":["1067-5027","1527-974X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the American Medical Informatics Association","raw_type":"journal-article"},{"id":"pmid:38904416","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/38904416","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":"Journal of the American Medical Informatics Association : JAMIA","raw_type":"Journal Article"},{"id":"pmh:oai:pubmedcentral.nih.gov:11339510","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11339510","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11339510/pdf/ocae147.pdf","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"J Am Med Inform Assoc","raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:pubmedcentral.nih.gov:11339510","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11339510","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11339510/pdf/ocae147.pdf","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"J Am Med Inform Assoc","raw_type":"Text"},"sustainable_development_goals":[{"score":0.5099999904632568,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G1922020763","display_name":"Detecting synergistic effects of pharmacological and non-pharmacological interventions for AD/ADRD","funder_award_id":"1r01ag078154-01","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G2473746854","display_name":null,"funder_award_id":"R01 AG078154","funder_id":"https://openalex.org/F4320337337","funder_display_name":"National Institute on Aging"},{"id":"https://openalex.org/G2635792716","display_name":null,"funder_award_id":"R01AT009457","funder_id":"https://openalex.org/F4320337593","funder_display_name":"National Center for Complementary and Integrative Health"},{"id":"https://openalex.org/G5791301197","display_name":"A Translational Informatics Framework to Mine Efficacy and Safety of Dietary Supplements","funder_award_id":"5r01at009457-06","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G6788124466","display_name":null,"funder_award_id":"R01 CA287413","funder_id":"https://openalex.org/F4320337351","funder_display_name":"National Cancer Institute"}],"funders":[{"id":"https://openalex.org/F4320309636","display_name":"University of Minnesota","ror":"https://ror.org/03grvy078"},{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320337337","display_name":"National Institute on Aging","ror":"https://ror.org/049v75w11"},{"id":"https://openalex.org/F4320337351","display_name":"National Cancer Institute","ror":"https://ror.org/040gcmg81"},{"id":"https://openalex.org/F4320337593","display_name":"National Center for Complementary and Integrative Health","ror":"https://ror.org/00190t495"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4399889932.pdf","grobid_xml":"https://content.openalex.org/works/W4399889932.grobid-xml"},"referenced_works_count":16,"referenced_works":["https://openalex.org/W2170189740","https://openalex.org/W2768488789","https://openalex.org/W2911489562","https://openalex.org/W3046375318","https://openalex.org/W4283318325","https://openalex.org/W4319663047","https://openalex.org/W4384071683","https://openalex.org/W4384561707","https://openalex.org/W4385571451","https://openalex.org/W4386120650","https://openalex.org/W4387500346","https://openalex.org/W4387617694","https://openalex.org/W4388605937","https://openalex.org/W4393187333","https://openalex.org/W4394869910","https://openalex.org/W6857563048"],"related_works":["https://openalex.org/W2976808399","https://openalex.org/W2609844752","https://openalex.org/W2981341912","https://openalex.org/W4285246823","https://openalex.org/W2045408812","https://openalex.org/W4226278302","https://openalex.org/W4385734297","https://openalex.org/W4221160509","https://openalex.org/W2547211086","https://openalex.org/W2888033806"],"abstract_inverted_index":{"OBJECTIVE:":[0],"To":[1],"investigate":[2,92],"the":[3,68,101,105,108,112,145,174,185,197,204],"demonstration":[4,48],"in":[5,39,196,207,239],"large":[6],"language":[7],"models":[8],"(LLMs)":[9],"for":[10,51,151,220],"biomedical":[11,53,240],"relation":[12,241],"extraction.":[13,242],"This":[14,87],"study":[15,36],"introduces":[16],"a":[17,45,217],"framework":[18,88,110,215],"comprising":[19],"three":[20],"types":[21],"of":[22,47,107,182],"adaptive":[23,71,77,80,84,94,98,161],"tuning":[24,85,169],"methods":[25],"to":[26,90],"assess":[27],"their":[28],"impacts":[29],"and":[30,59,82,97,115,124,136,200,233],"effectiveness.":[31],"MATERIALS":[32],"AND":[33],"METHODS:":[34],"Our":[35,127],"was":[37],"conducted":[38],"two":[40],"phases.":[41],"Initially,":[42],"we":[43,66],"analyzed":[44],"range":[46],"components":[49],"vital":[50],"LLMs'":[52],"data":[54,209],"capabilities,":[55],"including":[56,75],"task":[57,95],"descriptions":[58,96],"examples,":[60],"experimenting":[61],"with":[62],"various":[63],"combinations.":[64],"Subsequently,":[65],"introduced":[67],"LLM":[69,222],"instruction-example":[70,83],"prompting":[72,236],"(LEAP)":[73],"framework,":[74,156],"instruction":[76,168],"tuning,":[78,81],"example":[79,160],"methods.":[86],"aims":[89],"systematically":[91],"both":[93],"examples":[99],"within":[100],"demonstration.":[102],"We":[103],"assessed":[104],"performance":[106,165],"LEAP":[109,155,214],"on":[111,184],"DDI,":[113],"ChemProt,":[114],"BioRED":[116,201],"datasets,":[117,202],"employing":[118],"LLMs":[119],"such":[120],"as":[121],"Llama2-7b,":[122],"Llama2-13b,":[123],"MedLLaMA_13B.":[125],"RESULTS:":[126],"findings":[128],"indicated":[129],"that":[130],"Instruction":[131,147],"+":[132,134,148],"Options":[133,149],"Example":[135],"its":[137,159],"expanded":[138],"form":[139],"substantially":[140],"improved":[141],"F1":[142,180],"scores":[143],"over":[144,166],"standard":[146],"mode":[150],"zero-shot":[152],"LLMs.":[153],"The":[154,213],"particularly":[157],"through":[158],"prompting,":[162],"demonstrated":[163],"superior":[164],"conventional":[167],"across":[170],"all":[171],"models.":[172],"Notably,":[173],"MedLLAMA_13B":[175],"model":[176],"achieved":[177],"an":[178],"exceptional":[179],"score":[181],"95.13":[183],"ChemProt":[186],"dataset":[187],"using":[188],"this":[189],"method.":[190],"Significant":[191],"improvements":[192],"were":[193],"also":[194],"observed":[195],"DDI":[198],"2013":[199],"confirming":[203],"method's":[205],"robustness":[206],"sophisticated":[208],"extraction":[210],"scenarios.":[211],"CONCLUSION:":[212],"offers":[216],"compelling":[218],"strategy":[219],"enhancing":[221],"training":[223],"strategies,":[224],"steering":[225],"away":[226],"from":[227],"extensive":[228],"fine-tuning":[229],"towards":[230],"more":[231],"dynamic":[232],"contextually":[234],"enriched":[235],"methodologies,":[237],"showcasing":[238]},"counts_by_year":[{"year":2026,"cited_by_count":8},{"year":2025,"cited_by_count":13},{"year":2024,"cited_by_count":7}],"updated_date":"2026-08-28T12:50:07.497085","created_date":"2025-10-10T00:00:00"}