{"id":"https://openalex.org/W7113896655","doi":"https://doi.org/10.1145/3765612.3767227","title":"MADSurv: An Uncertainty-Aware Framework for Multimodal Cancer Survival Analysis","display_name":"MADSurv: An Uncertainty-Aware Framework for Multimodal Cancer Survival Analysis","publication_year":2025,"publication_date":"2025-10-12","ids":{"openalex":"https://openalex.org/W7113896655","doi":"https://doi.org/10.1145/3765612.3767227"},"language":null,"primary_location":{"id":"doi:10.1145/3765612.3767227","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3765612.3767227","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3765612.3767227","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 16th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3765612.3767227","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Enshi Zhang","orcid":"https://orcid.org/0009-0000-1586-7801"},"institutions":[{"id":"https://openalex.org/I19700959","display_name":"Florida International University","ror":"https://ror.org/02gz6gg07","country_code":"US","type":"education","lineage":["https://openalex.org/I19700959"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Enshi Zhang","raw_affiliation_strings":["Florida International University, Miami, FL, USA"],"affiliations":[{"raw_affiliation_string":"Florida International University, Miami, FL, USA","institution_ids":["https://openalex.org/I19700959"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Varun Sai Raigir","orcid":"https://orcid.org/0009-0002-5444-1285"},"institutions":[{"id":"https://openalex.org/I2613432","display_name":"University of South Florida","ror":"https://ror.org/032db5x82","country_code":"US","type":"education","lineage":["https://openalex.org/I2613432"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Varun Sai Raigir","raw_affiliation_strings":["University of South Florida, Tampa, FL, USA"],"affiliations":[{"raw_affiliation_string":"University of South Florida, Tampa, FL, USA","institution_ids":["https://openalex.org/I2613432"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Christian Poellabauer","orcid":"https://orcid.org/0000-0002-0599-7941"},"institutions":[{"id":"https://openalex.org/I19700959","display_name":"Florida International University","ror":"https://ror.org/02gz6gg07","country_code":"US","type":"education","lineage":["https://openalex.org/I19700959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Christian Poellabauer","raw_affiliation_strings":["Florida International University, Miami, FL, USA"],"affiliations":[{"raw_affiliation_string":"Florida International University, Miami, FL, USA","institution_ids":["https://openalex.org/I19700959"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Adrian Kohut","orcid":"https://orcid.org/0009-0000-5016-8838"},"institutions":[{"id":"https://openalex.org/I2613432","display_name":"University of South Florida","ror":"https://ror.org/032db5x82","country_code":"US","type":"education","lineage":["https://openalex.org/I2613432"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Adrian Kohut","raw_affiliation_strings":["University of South Florida, Tampa, FL, USA"],"affiliations":[{"raw_affiliation_string":"University of South Florida, Tampa, FL, USA","institution_ids":["https://openalex.org/I2613432"]}]},{"author_position":"middle","author":{"id":null,"display_name":"John Michael Templeton","orcid":"https://orcid.org/0000-0002-7229-9975"},"institutions":[{"id":"https://openalex.org/I2613432","display_name":"University of South Florida","ror":"https://ror.org/032db5x82","country_code":"US","type":"education","lineage":["https://openalex.org/I2613432"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"John Michael Templeton","raw_affiliation_strings":["University of South Florida, Tampa, FL, USA"],"affiliations":[{"raw_affiliation_string":"University of South Florida, Tampa, FL, USA","institution_ids":["https://openalex.org/I2613432"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Ananda Mondal","orcid":"https://orcid.org/0000-0002-4005-9942"},"institutions":[{"id":"https://openalex.org/I19700959","display_name":"Florida International University","ror":"https://ror.org/02gz6gg07","country_code":"US","type":"education","lineage":["https://openalex.org/I19700959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ananda Mondal","raw_affiliation_strings":["Florida International University, Miami, FL, USA"],"affiliations":[{"raw_affiliation_string":"Florida International University, Miami, FL, USA","institution_ids":["https://openalex.org/I19700959"]}]},{"author_position":"last","author":{"id":null,"display_name":"Lexi Weintraub","orcid":"https://orcid.org/0009-0009-4406-1255"},"institutions":[{"id":"https://openalex.org/I2613432","display_name":"University of South Florida","ror":"https://ror.org/032db5x82","country_code":"US","type":"education","lineage":["https://openalex.org/I2613432"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lexi Weintraub","raw_affiliation_strings":["University of South Florida, Tampa, FL, USA"],"affiliations":[{"raw_affiliation_string":"University of South Florida, Tampa, FL, USA","institution_ids":["https://openalex.org/I2613432"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I19700959"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.80763722,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.7031999826431274,"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/T10862","display_name":"AI in cancer detection","score":0.7031999826431274,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.08569999784231186,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"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":0.041999999433755875,"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/survival-analysis","display_name":"Survival analysis","score":0.5149000287055969},{"id":"https://openalex.org/keywords/concordance","display_name":"Concordance","score":0.4853000044822693},{"id":"https://openalex.org/keywords/brier-score","display_name":"Brier score","score":0.4562000036239624},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.42989999055862427},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.423799991607666},{"id":"https://openalex.org/keywords/limiting","display_name":"Limiting","score":0.384799987077713},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.3312000036239624},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.3111000061035156}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5403000116348267},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5324000120162964},{"id":"https://openalex.org/C10515644","wikidata":"https://www.wikidata.org/wiki/Q543310","display_name":"Survival analysis","level":2,"score":0.5149000287055969},{"id":"https://openalex.org/C160798450","wikidata":"https://www.wikidata.org/wiki/Q4230870","display_name":"Concordance","level":2,"score":0.4853000044822693},{"id":"https://openalex.org/C35405484","wikidata":"https://www.wikidata.org/wiki/Q4967066","display_name":"Brier score","level":2,"score":0.4562000036239624},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.451200008392334},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.42989999055862427},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.423799991607666},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4138000011444092},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.384799987077713},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.3499999940395355},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.3312000036239624},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.3111000061035156},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.2978000044822693},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.2937999963760376},{"id":"https://openalex.org/C138958017","wikidata":"https://www.wikidata.org/wiki/Q190087","display_name":"Data type","level":2,"score":0.28220000863075256},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.2752000093460083},{"id":"https://openalex.org/C3019894029","wikidata":"https://www.wikidata.org/wiki/Q332823","display_name":"Overall survival","level":2,"score":0.2752000093460083},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.273499995470047},{"id":"https://openalex.org/C120060458","wikidata":"https://www.wikidata.org/wiki/Q10145","display_name":"Milestone","level":2,"score":0.26820001006126404},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.26589998602867126},{"id":"https://openalex.org/C32220436","wikidata":"https://www.wikidata.org/wiki/Q2072214","display_name":"Personalized medicine","level":2,"score":0.26499998569488525},{"id":"https://openalex.org/C66339696","wikidata":"https://www.wikidata.org/wiki/Q6089397","display_name":"Log-rank test","level":3,"score":0.2540000081062317},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.2533999979496002},{"id":"https://openalex.org/C2779466056","wikidata":"https://www.wikidata.org/wiki/Q107630651","display_name":"Time point","level":2,"score":0.2513999938964844}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3765612.3767227","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3765612.3767227","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3765612.3767227","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 16th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3765612.3767227","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3765612.3767227","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3765612.3767227","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 16th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320309360","display_name":"Florida Department of Health","ror":"https://ror.org/03e1xkn26"},{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320337351","display_name":"National Cancer Institute","ror":"https://ror.org/040gcmg81"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7113896655.pdf","grobid_xml":"https://content.openalex.org/works/W7113896655.grobid-xml"},"referenced_works_count":21,"referenced_works":["https://openalex.org/W1786407144","https://openalex.org/W2052825782","https://openalex.org/W2761668583","https://openalex.org/W2954499361","https://openalex.org/W2996092187","https://openalex.org/W3028304854","https://openalex.org/W3124459754","https://openalex.org/W3137675974","https://openalex.org/W3147894994","https://openalex.org/W3176016422","https://openalex.org/W3203898052","https://openalex.org/W3211402536","https://openalex.org/W4291021272","https://openalex.org/W4293241248","https://openalex.org/W4293861233","https://openalex.org/W4313065529","https://openalex.org/W4387951310","https://openalex.org/W4390872175","https://openalex.org/W4390872461","https://openalex.org/W4402716294","https://openalex.org/W4413147104"],"related_works":[],"abstract_inverted_index":{"Multimodal":[0],"learning":[1],"significantly":[2],"improves":[3],"cancer":[4,173],"survival":[5,71,159,194],"prediction":[6],"using":[7,182,201],"multiple":[8],"data":[9,29,120],"types":[10],"for":[11,118,141,161],"each":[12,28,142,198],"patient,":[13],"including":[14],"clinical":[15,81],"data,":[16],"pathological":[17],"images,":[18],"and":[19,64,114,128,213],"genomic":[20],"data.":[21],"However,":[22],"existing":[23],"works":[24],"often":[25],"assume":[26],"that":[27,137,209],"type":[30],"contributes":[31],"equally,":[32],"neglecting":[33],"potential":[34],"conflicting":[35],"or":[36],"unreliable":[37],"information":[38],"between":[39],"different":[40,172],"modalities":[41,136],"by":[42,131],"simply":[43],"concatenating":[44],"features":[45,113],"to":[46,58,94,125,148,177,217],"form":[47],"a":[48,149,156],"fused":[49],"representation.":[50],"In":[51,83,175],"addition,":[52],"current":[53],"frameworks":[54],"are":[55,138],"trained":[56],"only":[57],"rank":[59],"relative":[60],"risk":[61,152,181],"among":[62],"patients":[63],"cannot":[65],"quantify":[66],"the":[67,88,135,183,189,192,202],"actual":[68],"likelihood":[69],"of":[70,158,191],"at":[72],"specific":[73],"time":[74],"points,":[75],"limiting":[76],"their":[77,115],"utility":[78],"in":[79,105,146],"real-world":[80],"settings.":[82],"this":[84],"work,":[85],"we":[86,186],"propose":[87],"Modality-Aware":[89],"Discrete-Time":[90],"Survival":[91],"(MADSurv)":[92],"framework":[93],"address":[95],"these":[96],"gaps.":[97],"First,":[98],"it":[99],"implements":[100],"an":[101],"uncertainty-aware":[102],"attention":[103],"mechanism":[104],"which":[106],"modality-specific":[107],"expert":[108],"encoders":[109],"learn":[110],"both":[111],"predictive":[112],"own":[116],"confidence":[117],"intelligent":[119],"fusion.":[121],"This":[122],"approach":[123],"leads":[124],"more":[126],"robust":[127],"personalized":[129],"predictions":[130],"dynamically":[132],"focusing":[133],"on":[134,170,197],"most":[139],"reliable":[140],"individual":[143],"patient.":[144],"Second,":[145],"addition":[147,176],"single":[150],"overall":[151,180],"score,":[153],"MADSurv":[154,210],"produces":[155],"sequence":[157],"probabilities":[160],"discrete":[162],"yearly":[163,199],"intervals.":[164],"We":[165],"evaluated":[166],"our":[167],"proposed":[168],"method":[169],"five":[171],"datasets.":[174],"ranking":[178],"patients'":[179],"concordance":[184],"index,":[185],"also":[187],"assessed":[188],"accuracy":[190],"model's":[193],"probability":[195],"estimates":[196],"milestone":[200],"Brier":[203],"score.":[204],"Our":[205],"experimental":[206],"results":[207],"demonstrate":[208],"achieves":[211],"superior":[212],"competitive":[214],"performance":[215],"compared":[216],"state-of-the-art":[218],"methods.":[219]},"counts_by_year":[],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-12-11T00:00:00"}