{"id":"https://openalex.org/W4409158465","doi":"https://doi.org/10.1145/3690624.3709232","title":"Advancing Confidence Calibration and Quantification in Medication Recommendation","display_name":"Advancing Confidence Calibration and Quantification in Medication Recommendation","publication_year":2025,"publication_date":"2025-04-04","ids":{"openalex":"https://openalex.org/W4409158465","doi":"https://doi.org/10.1145/3690624.3709232"},"language":"en","primary_location":{"id":"doi:10.1145/3690624.3709232","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3690624.3709232","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.1","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5113840820","display_name":"Qiang Chen","orcid":"https://orcid.org/0009-0008-1528-230X"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qianyu Chen","raw_affiliation_strings":["Beijing Institute of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100354072","display_name":"Xin Li","orcid":"https://orcid.org/0000-0003-4257-4347"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Li","raw_affiliation_strings":["Beijing Institute of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102927179","display_name":"Yujie Fang","orcid":"https://orcid.org/0000-0002-7613-4449"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yujie Fang","raw_affiliation_strings":["Beijing Institute of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055998640","display_name":"Mingzhong Wang","orcid":"https://orcid.org/0000-0002-6533-8104"},"institutions":[{"id":"https://openalex.org/I174025329","display_name":"University of the Sunshine Coast","ror":"https://ror.org/016gb9e15","country_code":"AU","type":"education","lineage":["https://openalex.org/I174025329"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Mingzhong Wang","raw_affiliation_strings":["University of the Sunshine Coast, Sippy Downs, QLD, Australia"],"affiliations":[{"raw_affiliation_string":"University of the Sunshine Coast, Sippy Downs, QLD, Australia","institution_ids":["https://openalex.org/I174025329"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5113840820"],"corresponding_institution_ids":["https://openalex.org/I125839683"],"apc_list":null,"apc_paid":null,"fwci":2.7855,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.89813413,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"106","last_page":"117"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.9980999827384949,"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":0.9980999827384949,"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/T11235","display_name":"Statistical Methods in Clinical Trials","score":0.968500018119812,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10350","display_name":"Electronic Health Records Systems","score":0.9315999746322632,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/calibration","display_name":"Calibration","score":0.7001897692680359},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5515038967132568},{"id":"https://openalex.org/keywords/confidence-interval","display_name":"Confidence interval","score":0.47525689005851746},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3665972948074341},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.346067875623703},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2671765685081482},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12761437892913818},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.12517225742340088}],"concepts":[{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.7001897692680359},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5515038967132568},{"id":"https://openalex.org/C44249647","wikidata":"https://www.wikidata.org/wiki/Q208498","display_name":"Confidence interval","level":2,"score":0.47525689005851746},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3665972948074341},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.346067875623703},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2671765685081482},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12761437892913818},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.12517225742340088}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3690624.3709232","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3690624.3709232","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.1","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1521746852","https://openalex.org/W2744140371","https://openalex.org/W2757504960","https://openalex.org/W2886476107","https://openalex.org/W2964068143","https://openalex.org/W2973201950","https://openalex.org/W2983825113","https://openalex.org/W3022922861","https://openalex.org/W3099958847","https://openalex.org/W3183048323","https://openalex.org/W3189998517","https://openalex.org/W3195483305","https://openalex.org/W3217263138","https://openalex.org/W4290927771","https://openalex.org/W4367047209","https://openalex.org/W4367663293","https://openalex.org/W4382239162","https://openalex.org/W4385076068","https://openalex.org/W4386473007","https://openalex.org/W4388052771","https://openalex.org/W4389610010","https://openalex.org/W6600076646","https://openalex.org/W6600239251","https://openalex.org/W6600248585"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Medication":[0],"recommendation":[1],"(MR)":[2],"has":[3],"undergone":[4],"rapid":[5],"advancement":[6],"in":[7,16,32,48,138,186],"recent":[8],"years,":[9],"driven":[10],"by":[11],"its":[12],"significant":[13],"practical":[14],"implications":[15],"healthcare.":[17],"However,":[18],"such":[19],"high-risk":[20],"scenarios":[21],"still":[22],"experience":[23],"two":[24,63],"critical":[25],"yet":[26],"overlooked":[27],"challenges:":[28],"the":[29,39,54,68,84,112,124,152,160,173,180],"prevalent":[30],"overconfidence":[31],"raw":[33],"confidence":[34,46,85,109,126],"for":[35,45,83,123,133,182],"individual":[36,87],"medications":[37],"and":[38,97,104,147,162],"lack":[40],"of":[41,71,86,114,127,164,175],"a":[42],"robust":[43],"solution":[44],"quantification":[47,121],"medication":[49,115,128],"combinations.":[50],"This":[51],"paper":[52],"represents":[53],"first":[55],"in-depth":[56],"study":[57],"addressing":[58],"this":[59],"gap.":[60],"We":[61],"introduce":[62],"innovative":[64],"methodologies":[65],"tailored":[66],"to":[67,110],"unique":[69],"challenges":[70],"MR":[72,143,176],"scenarios:":[73],"1)":[74],"A":[75,119],"discernible":[76],"binning-based":[77],"calibration":[78,103],"method":[79,122],"with":[80],"theoretical":[81],"guarantees":[82,90],"medication.":[88],"It":[89],"distinct":[91],"accuracy":[92],"levels":[93],"between":[94],"adjacent":[95],"bins":[96],"maintains":[98],"consistent":[99],"statistical":[100],"reliability":[101,174],"across":[102],"test":[105],"data,":[106],"enabling":[107],"calibrated":[108],"reflect":[111],"correctness":[113],"recommendations":[116],"distinctively.":[117],"2)":[118],"sample-based":[120],"set":[125],"combination,":[129],"which":[130],"is":[131],"applicable":[132],"various":[134],"existing":[135],"performance":[136],"metrics":[137],"MR.":[139],"Utilizing":[140],"representative":[141],"deep":[142],"models":[144],"as":[145],"backbones":[146],"conducting":[148],"extensive":[149],"experiments":[150],"on":[151],"widely":[153],"recognized":[154],"MIMIC":[155],"datasets,":[156],"we":[157],"empirically":[158],"prove":[159],"effectiveness":[161],"robustness":[163],"our":[165],"proposed":[166],"methods.":[167],"Our":[168],"approaches":[169],"not":[170],"only":[171],"improve":[172],"but":[177],"also":[178],"pave":[179],"way":[181],"more":[183],"informed":[184],"decision-making":[185],"clinical":[187],"settings.":[188]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-03-10T16:38:18.471706","created_date":"2025-10-10T00:00:00"}
