{"id":"https://openalex.org/W7126070904","doi":"https://doi.org/10.1109/bibm66473.2025.11356896","title":"Genomics-Aware Multimodal Self-Supervised Learning for Cancer Survival Prediction","display_name":"Genomics-Aware Multimodal Self-Supervised Learning for Cancer Survival Prediction","publication_year":2025,"publication_date":"2025-12-15","ids":{"openalex":"https://openalex.org/W7126070904","doi":"https://doi.org/10.1109/bibm66473.2025.11356896"},"language":null,"primary_location":{"id":"doi:10.1109/bibm66473.2025.11356896","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11356896","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","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/A5100976957","display_name":"Kaiwen Sun","orcid":null},"institutions":[{"id":"https://openalex.org/I4392738276","display_name":"State Key Laboratory of Virtual Reality Technology and Systems","ror":"https://ror.org/0009eea46","country_code":null,"type":"facility","lineage":["https://openalex.org/I4392738276","https://openalex.org/I82880672"]},{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Kaiwen Sun","raw_affiliation_strings":["Beihang University,State Key Laboratory of Virtual Reality Technology and Systems,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Beihang University,State Key Laboratory of Virtual Reality Technology and Systems,Beijing,China","institution_ids":["https://openalex.org/I82880672","https://openalex.org/I4392738276"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124210967","display_name":"Yuting Guo","orcid":null},"institutions":[{"id":"https://openalex.org/I78675632","display_name":"Beijing Information Science & Technology University","ror":"https://ror.org/04xnqep60","country_code":"CN","type":"education","lineage":["https://openalex.org/I78675632"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuting Guo","raw_affiliation_strings":["School of Computer Science, Beijing Information Science and Technology University,Beijing,China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Beijing Information Science and Technology University,Beijing,China","institution_ids":["https://openalex.org/I78675632"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036426775","display_name":"Yuanbo He","orcid":"https://orcid.org/0000-0001-8656-4496"},"institutions":[{"id":"https://openalex.org/I4210091706","display_name":"Henan Academy of Sciences","ror":"https://ror.org/00hy87220","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210091706"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanbo He","raw_affiliation_strings":["Institute of Electrophysiology, Henan Academy of Innovations in Medical Science,Zhengzhou,China"],"affiliations":[{"raw_affiliation_string":"Institute of Electrophysiology, Henan Academy of Innovations in Medical Science,Zhengzhou,China","institution_ids":["https://openalex.org/I4210091706"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124266420","display_name":"Zining Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I200296433","display_name":"Chinese Academy of Medical Sciences & Peking Union Medical College","ror":"https://ror.org/02drdmm93","country_code":"CN","type":"education","lineage":["https://openalex.org/I200296433"]},{"id":"https://openalex.org/I4210089431","display_name":"National Cancer Center","ror":"https://ror.org/0065zqt33","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I4210089431"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Zining Liu","raw_affiliation_strings":["National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences &#x0026; Peking Union Medical College,Department of Gynecologic Oncology,Beijing,China"],"affiliations":[{"raw_affiliation_string":"National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences &#x0026; Peking Union Medical College,Department of Gynecologic Oncology,Beijing,China","institution_ids":["https://openalex.org/I4210089431","https://openalex.org/I200296433"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101451138","display_name":"Jiahao Cui","orcid":"https://orcid.org/0009-0009-6981-4890"},"institutions":[{"id":"https://openalex.org/I4392738276","display_name":"State Key Laboratory of Virtual Reality Technology and Systems","ror":"https://ror.org/0009eea46","country_code":null,"type":"facility","lineage":["https://openalex.org/I4392738276","https://openalex.org/I82880672"]},{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiahao Cui","raw_affiliation_strings":["Beihang University,State Key Laboratory of Virtual Reality Technology and Systems,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Beihang University,State Key Laboratory of Virtual Reality Technology and Systems,Beijing,China","institution_ids":["https://openalex.org/I82880672","https://openalex.org/I4392738276"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100424095","display_name":"Shuai Li","orcid":"https://orcid.org/0000-0001-6266-2593"},"institutions":[{"id":"https://openalex.org/I4392738276","display_name":"State Key Laboratory of Virtual Reality Technology and Systems","ror":"https://ror.org/0009eea46","country_code":null,"type":"facility","lineage":["https://openalex.org/I4392738276","https://openalex.org/I82880672"]},{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuai Li","raw_affiliation_strings":["Beihang University,State Key Laboratory of Virtual Reality Technology and Systems,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Beihang University,State Key Laboratory of Virtual Reality Technology and Systems,Beijing,China","institution_ids":["https://openalex.org/I82880672","https://openalex.org/I4392738276"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100976957"],"corresponding_institution_ids":["https://openalex.org/I4392738276","https://openalex.org/I82880672"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.87381082,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2817","last_page":"2824"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9830999970436096,"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":0.9830999970436096,"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":0.0017000000225380063,"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/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.001500000013038516,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/feature","display_name":"Feature (linguistics)","score":0.49889999628067017},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.46549999713897705},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.43140000104904175},{"id":"https://openalex.org/keywords/genomics","display_name":"Genomics","score":0.4138000011444092},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4034000039100647},{"id":"https://openalex.org/keywords/fuse","display_name":"Fuse (electrical)","score":0.35040000081062317},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.33379998803138733},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3059000074863434}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6700000166893005},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6323999762535095},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5839999914169312},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.49889999628067017},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.46549999713897705},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.43140000104904175},{"id":"https://openalex.org/C189206191","wikidata":"https://www.wikidata.org/wiki/Q222046","display_name":"Genomics","level":4,"score":0.4138000011444092},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4034000039100647},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.35040000081062317},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.33379998803138733},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3059000074863434},{"id":"https://openalex.org/C2777522853","wikidata":"https://www.wikidata.org/wiki/Q5276128","display_name":"Digital pathology","level":2,"score":0.30300000309944153},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.2980000078678131},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.2906000018119812},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.28060001134872437},{"id":"https://openalex.org/C207886595","wikidata":"https://www.wikidata.org/wiki/Q1456138","display_name":"Pathological","level":2,"score":0.26919999718666077},{"id":"https://openalex.org/C2780910867","wikidata":"https://www.wikidata.org/wiki/Q1952416","display_name":"Multimodality","level":2,"score":0.2685000002384186},{"id":"https://openalex.org/C163763905","wikidata":"https://www.wikidata.org/wiki/Q17075943","display_name":"Precision medicine","level":2,"score":0.266400009393692},{"id":"https://openalex.org/C2776289891","wikidata":"https://www.wikidata.org/wiki/Q1931511","display_name":"Neglect","level":2,"score":0.26179999113082886},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.2587999999523163},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.25760000944137573}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm66473.2025.11356896","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11356896","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","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":23,"referenced_works":["https://openalex.org/W2056628299","https://openalex.org/W2366536035","https://openalex.org/W3011132328","https://openalex.org/W3043535018","https://openalex.org/W3135547872","https://openalex.org/W3173365702","https://openalex.org/W3203898052","https://openalex.org/W3214095426","https://openalex.org/W4224254299","https://openalex.org/W4291021272","https://openalex.org/W4292325804","https://openalex.org/W4304014045","https://openalex.org/W4387211504","https://openalex.org/W4387211638","https://openalex.org/W4387211745","https://openalex.org/W4387259074","https://openalex.org/W4390872175","https://openalex.org/W4390872461","https://openalex.org/W4390971224","https://openalex.org/W4402302443","https://openalex.org/W4402716294","https://openalex.org/W4406238213","https://openalex.org/W4406271223"],"related_works":[],"abstract_inverted_index":{"Survival":[0],"prediction":[1],"in":[2,57],"cancer":[3],"diagnosis":[4],"is":[5,156],"a":[6,25,67,76,107,127],"critical":[7],"research":[8],"task.":[9],"Current":[10],"methods":[11],"often":[12],"employ":[13],"the":[14,36,47,117,123,137],"multimodal":[15,77],"feature":[16],"fusion":[17],"of":[18,39,42,82,140],"pathological":[19,54,95],"images":[20],"and":[21,45,53,85,98,121],"genomics":[22,51,104],"data":[23,52],"within":[24],"weakly-supervised":[26],"learning":[27,81],"paradigm.":[28],"However,":[29],"these":[30,63],"approaches":[31],"fail":[32],"to":[33,116,144],"efficiently":[34],"learn":[35],"intrinsic":[37],"features":[38,84,97],"large":[40],"amount":[41],"unlabeled":[43],"WSIs":[44],"neglect":[46],"strong":[48],"associations":[49],"between":[50],"images,":[55],"resulting":[56],"reduced":[58],"prognostic":[59],"accuracy.":[60],"To":[61],"address":[62],"challenges,":[64],"we":[65,92,112],"propose":[66],"novel":[68],"Genomics-Aware":[69],"Multimodal":[70],"Self-Supervised":[71],"Learning":[72],"model":[73],"that":[74],"designs":[75],"pretext":[78],"task,":[79],"improving":[80],"intra-modal":[83],"inter-modal":[86],"correlations":[87],"without":[88],"additional":[89],"annotations.":[90],"Specifically,":[91],"randomly":[93],"mask":[94,114],"patch":[96],"fuse":[99],"unmasked":[100],"pathology":[101,119],"representations":[102,105],"with":[103],"via":[106,126],"cross-modal":[108],"attention":[109],"module.":[110],"Then":[111],"add":[113],"tokens":[115],"genomicsguided":[118],"representation":[120],"reconstruct":[122],"missing":[124],"parts":[125],"reconstruction":[128],"decoder.":[129],"Experimental":[130],"results":[131],"on":[132],"four":[133],"TCGA":[134],"datasets":[135],"demonstrate":[136],"superior":[138],"performance":[139],"our":[141],"method":[142],"compared":[143],"state-of-the-art":[145],"methods,":[146],"highlighting":[147],"its":[148],"potential":[149],"for":[150],"advancing":[151],"survival":[152],"prediction.":[153],"Our":[154],"code":[155],"available":[157],"at":[158],"https://github.com/sunkevin101/GMSL.":[159]},"counts_by_year":[],"updated_date":"2026-02-01T03:34:12.195049","created_date":"2026-01-30T00:00:00"}
