{"id":"https://openalex.org/W4408303059","doi":"https://doi.org/10.1145/3723049","title":"SQUIREDL: Sparse Sequence-to-Sequence Uncertainty Estimation in Evidential Deep Learning","display_name":"SQUIREDL: Sparse Sequence-to-Sequence Uncertainty Estimation in Evidential Deep Learning","publication_year":2025,"publication_date":"2025-03-11","ids":{"openalex":"https://openalex.org/W4408303059","doi":"https://doi.org/10.1145/3723049"},"language":"en","primary_location":{"id":"doi:10.1145/3723049","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3723049","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3723049","source":{"id":"https://openalex.org/S4210174653","display_name":"ACM Transactions on Computing for Healthcare","issn_l":"2637-8051","issn":["2637-8051","2691-1957"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Computing for Healthcare","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3723049","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5093459966","display_name":"Sotirios Vavaroutas","orcid":"https://orcid.org/0009-0005-8106-1634"},"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":"Sotirios Vavaroutas","raw_affiliation_strings":["University of Cambridge, Cambridge, United Kingdom","University of Cambridge, UK"],"raw_orcid":"https://orcid.org/0009-0005-8106-1634","affiliations":[{"raw_affiliation_string":"University of Cambridge, Cambridge, United Kingdom","institution_ids":["https://openalex.org/I241749"]},{"raw_affiliation_string":"University of Cambridge, UK","institution_ids":["https://openalex.org/I241749"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071116593","display_name":"Ting Dang","orcid":"https://orcid.org/0000-0003-3806-1493"},"institutions":[{"id":"https://openalex.org/I165779595","display_name":"The University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Ting Dang","raw_affiliation_strings":["The University of Melbourne, Melbourne, Australia","The University of Melbourne, Australia"],"raw_orcid":"https://orcid.org/0000-0003-3806-1493","affiliations":[{"raw_affiliation_string":"The University of Melbourne, Melbourne, Australia","institution_ids":["https://openalex.org/I165779595"]},{"raw_affiliation_string":"The University of Melbourne, Australia","institution_ids":["https://openalex.org/I165779595"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090930930","display_name":"Emma Rocheteau","orcid":"https://orcid.org/0000-0002-6450-0878"},"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":"Emma Rocheteau","raw_affiliation_strings":["University of Cambridge, Cambridge, United Kingdom","University of Cambridge, UK"],"raw_orcid":"https://orcid.org/0000-0002-6450-0878","affiliations":[{"raw_affiliation_string":"University of Cambridge, Cambridge, United Kingdom","institution_ids":["https://openalex.org/I241749"]},{"raw_affiliation_string":"University of Cambridge, UK","institution_ids":["https://openalex.org/I241749"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010623957","display_name":"Cecilia Mascolo","orcid":"https://orcid.org/0000-0001-9614-4380"},"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":"Cecilia Mascolo","raw_affiliation_strings":["University of Cambridge, Cambridge, United Kingdom","University of Cambridge, UK"],"raw_orcid":"https://orcid.org/0000-0001-9614-4380","affiliations":[{"raw_affiliation_string":"University of Cambridge, Cambridge, United Kingdom","institution_ids":["https://openalex.org/I241749"]},{"raw_affiliation_string":"University of Cambridge, UK","institution_ids":["https://openalex.org/I241749"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.792,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.89935579,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"6","issue":"3","first_page":"1","last_page":"21"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.9990000128746033,"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":0.9990000128746033,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9966999888420105,"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":0.9955999851226807,"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/sequence","display_name":"Sequence (biology)","score":0.7058542966842651},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5822477340698242},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.44894951581954956},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42165136337280273},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3450376093387604},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.10850828886032104},{"id":"https://openalex.org/keywords/genetics","display_name":"Genetics","score":0.06881904602050781}],"concepts":[{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.7058542966842651},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5822477340698242},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.44894951581954956},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42165136337280273},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3450376093387604},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.10850828886032104},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.06881904602050781}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3723049","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3723049","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3723049","source":{"id":"https://openalex.org/S4210174653","display_name":"ACM Transactions on Computing for Healthcare","issn_l":"2637-8051","issn":["2637-8051","2691-1957"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Computing for Healthcare","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1145/3723049","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3723049","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3723049","source":{"id":"https://openalex.org/S4210174653","display_name":"ACM Transactions on Computing for Healthcare","issn_l":"2637-8051","issn":["2637-8051","2691-1957"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Computing for Healthcare","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4408303059.pdf"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W61940207","https://openalex.org/W204923336","https://openalex.org/W1971654961","https://openalex.org/W2040513229","https://openalex.org/W2064675550","https://openalex.org/W2065914903","https://openalex.org/W2125290126","https://openalex.org/W2129995532","https://openalex.org/W2146563690","https://openalex.org/W2322662949","https://openalex.org/W2577366047","https://openalex.org/W2787366713","https://openalex.org/W2810469995","https://openalex.org/W2963807318","https://openalex.org/W2964010366","https://openalex.org/W3025713978","https://openalex.org/W3042777221","https://openalex.org/W3049694150","https://openalex.org/W3092657637","https://openalex.org/W3093737097","https://openalex.org/W3112995907","https://openalex.org/W3161603458","https://openalex.org/W3167364308","https://openalex.org/W3183048323","https://openalex.org/W4296679852","https://openalex.org/W4300772090","https://openalex.org/W4302079941","https://openalex.org/W4306964096","https://openalex.org/W4309021794","https://openalex.org/W4382566490"],"related_works":["https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W4391375266","https://openalex.org/W1979597421","https://openalex.org/W2007980826","https://openalex.org/W2061531152","https://openalex.org/W3002753104","https://openalex.org/W2077600819","https://openalex.org/W2033914206","https://openalex.org/W2042327336"],"abstract_inverted_index":{"Machine":[0],"Learning":[1],"models":[2,131],"typically":[3],"assume":[4],"that":[5],"time":[6,56],"series":[7],"are":[8,22],"regularly":[9],"spaced;":[10],"however,":[11],"this":[12,25],"is":[13,138],"often":[14],"unrealistic":[15],"in":[16,132,140,175,182,192],"healthcare,":[17],"where":[18],"missing":[19,73],"data":[20,76,99],"recordings":[21],"common.":[23],"In":[24,144],"context,":[26],"uncertainty":[27,69,105,119],"estimates":[28],"play":[29],"a":[30,47,110,125,133,189],"pivotal":[31],"role,":[32],"as":[33],"they":[34],"can":[35],"enable":[36],"confident":[37],"and":[38,97,178],"non-confident":[39],"predictions":[40],"to":[41,71,95,101,128,152],"be":[42],"distinguished.":[43],"We":[44],"propose":[45],"SQUIREDL,":[46],"novel":[48],"uncertainty-aware":[49,177,196],"sequence-to-sequence":[50,122,150],"prediction":[51,151],"method":[52],"for":[53,68,114],"sparse":[54],"healthcare":[55],"series.":[57],"Specifically,":[58],"we":[59,83,108,148,187],"enhance":[60],"the":[61,85,116,130,154,164,193],"state-of-the-art":[62],"evidential":[63,89],"regression":[64,90],"framework,":[65],"widely":[66],"used":[67],"estimation,":[70],"handle":[72],"data.":[74],"Following":[75],"imputation":[77],"with":[78],"an":[79],"Akima":[80],"spline-based":[81],"method,":[82],"modify":[84],"loss":[86],"function":[87],"of":[88,112,118,195],"by":[91],"assigning":[92],"different":[93],"weights":[94],"imputed":[96],"observed":[98],"points,":[100],"offer":[102],"more":[103,170],"reliable":[104,126],"estimates.":[106],"Additionally,":[107],"examine":[109],"variety":[111],"metrics":[113],"assessing":[115],"success":[117],"estimations":[120],"on":[121],"predictions,":[123,197],"providing":[124],"way":[127],"evaluate":[129],"medical":[134],"setting.":[135],"Our":[136,161],"proposal":[137],"demonstrated":[139],"two":[141],"clinical":[142],"applications.":[143],"continuous":[145],"glucose":[146,158],"monitoring,":[147],"use":[149],"obtain":[153],"hypoglycaemia":[155],"risk":[156,167],"from":[157],"sensor":[159],"readings.":[160],"approach":[162],"captures":[163],"ground":[165],"truth":[166],"values":[168],"30%":[169],"accurately,":[171],"bringing":[172],"consistent":[173],"improvements":[174],"both":[176],"accuracy-based":[179],"metrics.":[180],"Similarly,":[181],"COVID-19":[183],"hospital":[184],"admissions":[185],"data,":[186],"achieve":[188],"22%":[190],"improvement":[191],"accuracy":[194],"enabling":[198],"better":[199],"resource":[200],"planning.":[201]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
