{"id":"https://openalex.org/W4401863908","doi":"https://doi.org/10.1145/3637528.3671586","title":"SepsisLab: Early Sepsis Prediction with Uncertainty Quantification and Active Sensing","display_name":"SepsisLab: Early Sepsis Prediction with Uncertainty Quantification and Active Sensing","publication_year":2024,"publication_date":"2024-08-24","ids":{"openalex":"https://openalex.org/W4401863908","doi":"https://doi.org/10.1145/3637528.3671586","pmid":"https://pubmed.ncbi.nlm.nih.gov/39399376"},"language":"en","primary_location":{"id":"doi:10.1145/3637528.3671586","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3637528.3671586","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11470769/pdf/nihms-2025919.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5036160994","display_name":"Changchang Yin","orcid":"https://orcid.org/0000-0002-6540-6365"},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Changchang Yin","raw_affiliation_strings":["The Ohio State University, Columbus, OH, USA"],"affiliations":[{"raw_affiliation_string":"The Ohio State University, Columbus, OH, USA","institution_ids":["https://openalex.org/I52357470"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065279279","display_name":"Ping\u2010Yu Chen","orcid":"https://orcid.org/0000-0002-3472-4221"},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pin-Yu Chen","raw_affiliation_strings":["IBM Research, Yorktown Heights, NY, USA"],"affiliations":[{"raw_affiliation_string":"IBM Research, Yorktown Heights, NY, USA","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033744502","display_name":"Bingsheng Yao","orcid":"https://orcid.org/0009-0004-8329-4610"},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bingsheng Yao","raw_affiliation_strings":["Northeastern University, Boston, MA, USA"],"affiliations":[{"raw_affiliation_string":"Northeastern University, Boston, MA, USA","institution_ids":["https://openalex.org/I12912129"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062817658","display_name":"Dakuo Wang","orcid":"https://orcid.org/0000-0001-9371-9441"},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dakuo Wang","raw_affiliation_strings":["Northeastern University, Boston, MA, USA"],"affiliations":[{"raw_affiliation_string":"Northeastern University, Boston, MA, USA","institution_ids":["https://openalex.org/I12912129"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000159448","display_name":"Jeffrey M. Caterino","orcid":"https://orcid.org/0009-0004-2512-4955"},"institutions":[{"id":"https://openalex.org/I2802841970","display_name":"The Ohio State University Wexner Medical Center","ror":"https://ror.org/00c01js51","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I2802841970"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jeffrey Caterino","raw_affiliation_strings":["The Ohio State University Wexner Medical Center, Columbus, OH, USA"],"affiliations":[{"raw_affiliation_string":"The Ohio State University Wexner Medical Center, Columbus, OH, USA","institution_ids":["https://openalex.org/I2802841970"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050360222","display_name":"Ping Zhang","orcid":"https://orcid.org/0000-0002-4601-0779"},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ping Zhang","raw_affiliation_strings":["The Ohio State University, Columbus, OH, USA"],"affiliations":[{"raw_affiliation_string":"The Ohio State University, Columbus, OH, USA","institution_ids":["https://openalex.org/I52357470"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5036160994"],"corresponding_institution_ids":["https://openalex.org/I52357470"],"apc_list":null,"apc_paid":null,"fwci":2.2674,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.88846539,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"2024","issue":null,"first_page":"6158","last_page":"6168"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10218","display_name":"Sepsis Diagnosis and Treatment","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10218","display_name":"Sepsis Diagnosis and Treatment","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"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":0.9970999956130981,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.948199987411499,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/imputation","display_name":"Imputation (statistics)","score":0.7615175247192383},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.7225296497344971},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5943953990936279},{"id":"https://openalex.org/keywords/confidence-interval","display_name":"Confidence interval","score":0.5671407580375671},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5377154350280762},{"id":"https://openalex.org/keywords/sepsis","display_name":"Sepsis","score":0.5213590860366821},{"id":"https://openalex.org/keywords/mean-squared-prediction-error","display_name":"Mean squared prediction error","score":0.4262073040008545},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.4112963080406189},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3671581745147705},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3514479994773865},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3510698676109314},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.26446297764778137},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15879705548286438}],"concepts":[{"id":"https://openalex.org/C58041806","wikidata":"https://www.wikidata.org/wiki/Q1660484","display_name":"Imputation (statistics)","level":3,"score":0.7615175247192383},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.7225296497344971},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5943953990936279},{"id":"https://openalex.org/C44249647","wikidata":"https://www.wikidata.org/wiki/Q208498","display_name":"Confidence interval","level":2,"score":0.5671407580375671},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5377154350280762},{"id":"https://openalex.org/C2778384902","wikidata":"https://www.wikidata.org/wiki/Q183134","display_name":"Sepsis","level":2,"score":0.5213590860366821},{"id":"https://openalex.org/C167085575","wikidata":"https://www.wikidata.org/wiki/Q6803654","display_name":"Mean squared prediction error","level":2,"score":0.4262073040008545},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.4112963080406189},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3671581745147705},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3514479994773865},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3510698676109314},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.26446297764778137},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15879705548286438},{"id":"https://openalex.org/C203014093","wikidata":"https://www.wikidata.org/wiki/Q101929","display_name":"Immunology","level":1,"score":0.0},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/3637528.3671586","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3637528.3671586","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"},{"id":"pmid:39399376","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/39399376","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":"KDD : proceedings. International Conference on Knowledge Discovery & Data Mining","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:11470769","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11470769","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11470769/pdf/nihms-2025919.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"KDD","raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:pubmedcentral.nih.gov:11470769","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11470769","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11470769/pdf/nihms-2025919.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"KDD","raw_type":"Text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.7799999713897705,"display_name":"Good health and well-being"}],"awards":[{"id":"https://openalex.org/G1640847642","display_name":null,"funder_award_id":"R01AI188576","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G3611247453","display_name":null,"funder_award_id":"R01GM","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G4569476262","display_name":null,"funder_award_id":"R01GM141279","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G5921281487","display_name":null,"funder_award_id":"number","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6755165505","display_name":null,"funder_award_id":"award","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7620595296","display_name":null,"funder_award_id":"2145625","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7816937986","display_name":null,"funder_award_id":"IIS-2145625","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G848032724","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320309374","display_name":"Ohio State University","ror":"https://ror.org/00rs6vg23"},{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4401863908.pdf","grobid_xml":"https://content.openalex.org/works/W4401863908.grobid-xml"},"referenced_works_count":31,"referenced_works":["https://openalex.org/W1484075671","https://openalex.org/W2006715371","https://openalex.org/W2039251546","https://openalex.org/W2064675550","https://openalex.org/W2069266605","https://openalex.org/W2150979970","https://openalex.org/W2169167455","https://openalex.org/W2280404143","https://openalex.org/W2396881363","https://openalex.org/W2599245417","https://openalex.org/W2742491462","https://openalex.org/W2768146862","https://openalex.org/W2793167996","https://openalex.org/W2905983446","https://openalex.org/W2963026800","https://openalex.org/W2964159205","https://openalex.org/W2990589708","https://openalex.org/W2995080835","https://openalex.org/W2995282027","https://openalex.org/W2997532515","https://openalex.org/W2997629435","https://openalex.org/W3003504112","https://openalex.org/W3024277754","https://openalex.org/W3046153892","https://openalex.org/W3080826732","https://openalex.org/W3102100346","https://openalex.org/W3118197078","https://openalex.org/W3123085258","https://openalex.org/W3138415243","https://openalex.org/W3164731060","https://openalex.org/W4212774754"],"related_works":["https://openalex.org/W2181530120","https://openalex.org/W4211215373","https://openalex.org/W2024529227","https://openalex.org/W2055961818","https://openalex.org/W1574575415","https://openalex.org/W3144172081","https://openalex.org/W3179858851","https://openalex.org/W3028371478","https://openalex.org/W2081476516","https://openalex.org/W2581984549"],"abstract_inverted_index":{"Sepsis":[0],"is":[1,80,214],"the":[2,9,20,49,55,70,84,90,102,131,144,149,176,182,211,217,224,258],"leading":[3],"cause":[4],"of":[5,22,52,95,133,219,265],"in-hospital":[6],"mortality":[7],"in":[8,43,48,62,67,111,185,197,260],"USA.":[10],"Early":[11],"sepsis":[12,23,103,116,240,253],"onset":[13],"prediction":[14,104,117,134,241,262],"and":[15,64,136,192,194,223,242,251,263],"diagnosis":[16,264],"could":[17],"significantly":[18],"improve":[19],"survival":[21],"patients.":[24],"Existing":[25],"predictive":[26,71],"models":[27,184],"are":[28],"usually":[29],"trained":[30],"on":[31,114,246],"high-quality":[32],"data":[33,189,196],"with":[34,87,153],"few":[35],"missing":[36,39,78],"information,":[37],"while":[38],"values":[40,79],"widely":[41],"exist":[42],"real-world":[44],"clinical":[45],"scenarios":[46],"(especially":[47],"first":[50,125],"hours":[51],"admissions":[53,220],"to":[54,76,101,142,157,167,174,221],"hospital),":[56],"which":[57,82,106],"causes":[58],"a":[59,162,235],"significant":[60],"decrease":[61],"accuracy":[63],"an":[65],"increase":[66,168],"uncertainty":[68,94,119,129,139,213],"for":[69,148,238],"models.":[72,249],"The":[73,93,198,206],"common":[74],"method":[75],"handle":[77],"imputation,":[81],"replaces":[83],"unavailable":[85],"variables":[86],"estimates":[88],"from":[89,257],"observed":[91],"data.":[92],"imputation":[96],"results":[97,208],"can":[98,255],"be":[99],"propagated":[100,128,145,212],"outputs,":[105],"have":[107],"not":[108],"been":[109],"studied":[110],"existing":[112],"works":[113],"either":[115],"or":[118],"quantification.":[120],"In":[121],"this":[122],"study,":[123],"we":[124,160,233],"define":[126],"such":[127],"as":[130],"variance":[132],"output":[135],"then":[137],"introduce":[138],"propagation":[140],"methods":[141],"quantify":[143],"uncertainty.":[146],"Moreover,":[147],"potential":[150,252],"high-risk":[151],"patients":[152,254],"low":[154],"confidence":[155,169],"due":[156],"limited":[158],"observations,":[159],"propose":[161],"robust":[163],"active":[164,229,243],"sensing":[165,230,244],"algorithm":[166,226],"by":[170],"actively":[171],"recommending":[172],"clinicians":[173],"observe":[175],"most":[177],"informative":[178],"variables.":[179],"We":[180],"validate":[181],"proposed":[183,225],"both":[186],"publicly":[187],"available":[188],"(i.e.,":[190],"MIMIC-III":[191],"AmsterdamUMCdb)":[193],"proprietary":[195],"Ohio":[199],"State":[200],"University":[201],"Wexner":[202],"Medical":[203],"Center":[204],"(OSUWMC).":[205],"experimental":[207],"show":[209],"that":[210],"dominant":[215],"at":[216],"beginning":[218],"hospitals":[222],"outperforms":[227],"state-of-the-art":[228],"methods.":[231],"Finally,":[232],"implement":[234],"SepsisLab":[236],"system":[237,259],"early":[239,261],"based":[245],"our":[247],"pre-trained":[248],"Clinicians":[250],"benefit":[256],"sepsis.":[266]},"counts_by_year":[{"year":2025,"cited_by_count":6}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}