{"id":"https://openalex.org/W7126037730","doi":"https://doi.org/10.1109/bibm66473.2025.11356124","title":"Beyond Fusion: Clinical Supervision as Semantic Anchor for Robust Omics-Based Survival Prediction","display_name":"Beyond Fusion: Clinical Supervision as Semantic Anchor for Robust Omics-Based Survival Prediction","publication_year":2025,"publication_date":"2025-12-15","ids":{"openalex":"https://openalex.org/W7126037730","doi":"https://doi.org/10.1109/bibm66473.2025.11356124"},"language":null,"primary_location":{"id":"doi:10.1109/bibm66473.2025.11356124","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11356124","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/A5100386685","display_name":"Yixin Liu","orcid":"https://orcid.org/0000-0002-9500-8333"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yaozhang Liu","raw_affiliation_strings":["School of Computer Science and Technology, Guangdong University of Technology,Guangzhou,China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Guangdong University of Technology,Guangzhou,China","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002425325","display_name":"Pengcheng Wang","orcid":"https://orcid.org/0000-0002-5282-236X"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Hu","raw_affiliation_strings":["School of Computer Science and Technology, Guangdong University of Technology,Guangzhou,China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Guangdong University of Technology,Guangzhou,China","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"last","author":{"id":null,"display_name":"Xiaoping Li","orcid":null},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoping Li","raw_affiliation_strings":["School of Computer Science and Technology, Guangdong University of Technology,Guangzhou,China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Guangdong University of Technology,Guangzhou,China","institution_ids":["https://openalex.org/I139024713"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100386685"],"corresponding_institution_ids":["https://openalex.org/I139024713"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.84039574,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2580","last_page":"2585"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.6976000070571899,"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":0.6976000070571899,"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/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.04259999841451645,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.03530000150203705,"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/benchmark","display_name":"Benchmark (surveying)","score":0.5830000042915344},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5630999803543091},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.5078999996185303},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4722999930381775},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.46720001101493835},{"id":"https://openalex.org/keywords/bridge","display_name":"Bridge (graph theory)","score":0.420199990272522},{"id":"https://openalex.org/keywords/modality","display_name":"Modality (human\u2013computer interaction)","score":0.4066999852657318},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.39969998598098755},{"id":"https://openalex.org/keywords/clinical-practice","display_name":"Clinical Practice","score":0.37869998812675476}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7075999975204468},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5830000042915344},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5745000243186951},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5630999803543091},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.5078999996185303},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5041999816894531},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4722999930381775},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.46720001101493835},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.426800012588501},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.420199990272522},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.4066999852657318},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.39969998598098755},{"id":"https://openalex.org/C2779974597","wikidata":"https://www.wikidata.org/wiki/Q28448986","display_name":"Clinical Practice","level":2,"score":0.37869998812675476},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.3418999910354614},{"id":"https://openalex.org/C116409475","wikidata":"https://www.wikidata.org/wiki/Q1385056","display_name":"External Data Representation","level":2,"score":0.3366999924182892},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.33149999380111694},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.32420000433921814},{"id":"https://openalex.org/C2779965156","wikidata":"https://www.wikidata.org/wiki/Q5227350","display_name":"Data sharing","level":3,"score":0.3149000108242035},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.31150001287460327},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.3028999865055084},{"id":"https://openalex.org/C72634772","wikidata":"https://www.wikidata.org/wiki/Q386824","display_name":"Data integration","level":2,"score":0.299699991941452},{"id":"https://openalex.org/C90312973","wikidata":"https://www.wikidata.org/wiki/Q7449052","display_name":"Semantic data model","level":2,"score":0.2903999984264374},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.2903999984264374},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2791000008583069},{"id":"https://openalex.org/C138958017","wikidata":"https://www.wikidata.org/wiki/Q190087","display_name":"Data type","level":2,"score":0.2662999927997589},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.25609999895095825},{"id":"https://openalex.org/C2779110517","wikidata":"https://www.wikidata.org/wiki/Q1240788","display_name":"Supervisor","level":2,"score":0.2556999921798706},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2549000084400177},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2531999945640564}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm66473.2025.11356124","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11356124","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":[{"display_name":"Reduced inequalities","score":0.688218891620636,"id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G5474350791","display_name":null,"funder_award_id":"62273089","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5986587901","display_name":null,"funder_award_id":"2017YFB1400801,2022YFB3305500,2022YFB3305500,62273089","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G776972200","display_name":null,"funder_award_id":"2025A1515010114","funder_id":"https://openalex.org/F4320337111","funder_display_name":"Basic and Applied Basic Research Foundation of Guangdong Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null},{"id":"https://openalex.org/F4320337111","display_name":"Basic and Applied Basic Research Foundation of Guangdong Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W2028236537","https://openalex.org/W2095463689","https://openalex.org/W2101234009","https://openalex.org/W2135046866","https://openalex.org/W2149199519","https://openalex.org/W2165759865","https://openalex.org/W2951209146","https://openalex.org/W2954499361","https://openalex.org/W3043242675","https://openalex.org/W3130672622","https://openalex.org/W3147894994","https://openalex.org/W4213164367","https://openalex.org/W4282980285","https://openalex.org/W4286542683","https://openalex.org/W4293241248","https://openalex.org/W4385406244","https://openalex.org/W4385968950","https://openalex.org/W4390613477","https://openalex.org/W4390991962","https://openalex.org/W4395660270","https://openalex.org/W4399390205","https://openalex.org/W4408845629"],"related_works":[],"abstract_inverted_index":{"Accurate":[0],"cancer":[1,178],"survival":[2],"prediction":[3],"based":[4],"on":[5,175],"multiomics":[6],"data":[7,27,59,85,120,135],"is":[8,196],"critical":[9],"for":[10],"clinical":[11,30,58,65,84,119,134],"decision-making":[12],"and":[13,28,45,60,146],"personalized":[14],"oncology,":[15],"yet":[16],"remains":[17],"challenging":[18],"due":[19],"to":[20,71,148],"the":[21,35,52,73,99,181],"complex":[22],"interplay":[23],"between":[24,161],"high-dimensional":[25],"multi-omics":[26],"heterogeneous":[29],"factors.":[31],"While":[32],"most":[33],"of":[34,63,101,183],"existing":[36],"methods":[37],"have":[38],"made":[39],"progress":[40],"by":[41],"integrating":[42],"omics-specific":[43],"features":[44],"modeling":[46],"cross-view":[47],"interactions,":[48],"they":[49],"fundamentally":[50],"neglect":[51],"prognostic":[53],"semantic":[54,75],"richness":[55],"embedded":[56],"in":[57,169,188],"fall":[61],"short":[62],"exploiting":[64],"information":[66],"as":[67,122,127],"a":[68,87,111,123,128,154,170],"supervisory":[69,95],"signal":[70,96],"bridge":[72],"clinic-omics":[74],"gap.":[76],"Drawing":[77],"inspiration":[78],"from":[79,86],"CLIP,":[80],"we":[81,109],"transform":[82],"structured":[83,133],"passive":[88],"input":[89],"modality":[90],"into":[91,138],"an":[92],"active,":[93],"textual":[94,139],"that":[97,117,158],"shapes":[98],"learning":[100,152],"more":[102],"discriminative":[103],"omics":[104,150],"representations.":[105],"To":[106],"address":[107],"this,":[108],"propose":[110],"Clinic-Omics":[112],"Representation":[113],"Alignment":[114],"(CORA)":[115],"Module":[116],"reframes":[118],"not":[121],"direct":[124],"input,":[125],"but":[126],"contrastive":[129],"supervision":[130],"mechanism.":[131],"Specifically,":[132],"are":[136],"transformed":[137],"descriptors,":[140],"encoded":[141],"via":[142],"pretrained":[143],"language":[144],"models,":[145],"used":[147],"guide":[149],"feature":[151],"through":[153],"CLIP-inspired":[155],"alignment":[156],"objective":[157],"minimizes":[159],"distances":[160],"matched":[162],"clinicalomics":[163],"pairs":[164,168],"while":[165],"separating":[166],"mismatched":[167],"shared":[171],"latent":[172],"space.":[173],"Experiments":[174],"seven":[176],"benchmark":[177],"dataset":[179],"demonstrate":[180],"effectiveness":[182],"incorporating":[184],"our":[185],"proposed":[186],"module":[187],"comparison":[189],"with":[190],"several":[191],"recent":[192],"baselines.":[193],"The":[194],"code":[195],"available":[197],"at":[198],"https://github.com/LYZ1222/CORA":[199]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2026-01-30T00:00:00"}