{"id":"https://openalex.org/W4414360653","doi":"https://doi.org/10.24963/ijcai.2025/149","title":"Curriculum Hierarchical Knowledge Distillation for Bias-Free Survival Prediction","display_name":"Curriculum Hierarchical Knowledge Distillation for Bias-Free Survival Prediction","publication_year":2025,"publication_date":"2025-09-01","ids":{"openalex":"https://openalex.org/W4414360653","doi":"https://doi.org/10.24963/ijcai.2025/149"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2025/149","is_oa":false,"landing_page_url":"https://doi.org/10.24963/ijcai.2025/149","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence","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/A5037831162","display_name":"Chaozhuo Li","orcid":"https://orcid.org/0000-0002-9867-1712"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chaozhuo Li","raw_affiliation_strings":["Beijing University of Posts and Telecommunications"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004991045","display_name":"Zhihao Tang","orcid":"https://orcid.org/0000-0003-1893-5421"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhihao Tang","raw_affiliation_strings":["Beijing University of Posts and Telecommunications"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046256612","display_name":"Mingji Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I129708740","display_name":"Fujian Medical University","ror":"https://ror.org/050s6ns64","country_code":"CN","type":"education","lineage":["https://openalex.org/I129708740"]},{"id":"https://openalex.org/I4210148548","display_name":"Fujian Provincial Cancer Hospital","ror":"https://ror.org/058ms9w43","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210148548"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingji Zhang","raw_affiliation_strings":["Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital","institution_ids":["https://openalex.org/I4210148548","https://openalex.org/I129708740"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100608598","display_name":"Zhiquan Liu","orcid":"https://orcid.org/0000-0003-4917-7686"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhiquan Liu","raw_affiliation_strings":["Jinan University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jinan University","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101599254","display_name":"Litian Zhang","orcid":"https://orcid.org/0000-0002-6981-3873"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Litian Zhang","raw_affiliation_strings":["Beijing University of Posts and Telecommunications"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100672722","display_name":"Xi Zhang","orcid":"https://orcid.org/0000-0002-2111-7385"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xi Zhang","raw_affiliation_strings":["Beijing University of Posts and Telecommunications"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5037831162"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12242702,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1332","last_page":"1340"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.8952999711036682,"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":0.8952999711036682,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.867900013923645,"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/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.8636999726295471,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5525000095367432},{"id":"https://openalex.org/keywords/scarcity","display_name":"Scarcity","score":0.5013999938964844},{"id":"https://openalex.org/keywords/independent-and-identically-distributed-random-variables","display_name":"Independent and identically distributed random variables","score":0.35120001435279846},{"id":"https://openalex.org/keywords/curriculum","display_name":"Curriculum","score":0.33309999108314514},{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.3249000012874603},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.31529998779296875}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6425999999046326},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6184999942779541},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5972999930381775},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5525000095367432},{"id":"https://openalex.org/C109747225","wikidata":"https://www.wikidata.org/wiki/Q815758","display_name":"Scarcity","level":2,"score":0.5013999938964844},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37529999017715454},{"id":"https://openalex.org/C141513077","wikidata":"https://www.wikidata.org/wiki/Q378542","display_name":"Independent and identically distributed random variables","level":3,"score":0.35120001435279846},{"id":"https://openalex.org/C47177190","wikidata":"https://www.wikidata.org/wiki/Q207137","display_name":"Curriculum","level":2,"score":0.33309999108314514},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.3249000012874603},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.31529998779296875},{"id":"https://openalex.org/C144986985","wikidata":"https://www.wikidata.org/wiki/Q871236","display_name":"Hierarchical database model","level":2,"score":0.30709999799728394},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.2831000089645386},{"id":"https://openalex.org/C2778334786","wikidata":"https://www.wikidata.org/wiki/Q1586270","display_name":"Variation (astronomy)","level":2,"score":0.25600001215934753},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.2551000118255615}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2025/149","is_oa":false,"landing_page_url":"https://doi.org/10.24963/ijcai.2025/149","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence","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":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Survival":[0],"prediction":[1,138],"is":[2,145],"a":[3,11,87,115],"pivotal":[4],"task":[5],"for":[6,76],"estimating":[7],"mortality":[8],"risk":[9],"within":[10],"given":[12],"timeframe":[13],"based":[14,91],"on":[15,92],"whole":[16],"slide":[17],"images":[18],"(WSIs).":[19],"Conventional":[20],"models":[21],"typically":[22],"assume":[23],"that":[24,35],"WSIs":[25,66],"across":[26,67,140],"patients":[27,78],"are":[28],"independent":[29],"and":[30,46,63,72,102,133,151],"identically":[31],"distributed,":[32],"an":[33],"assumption":[34],"may":[36],"not":[37],"hold":[38],"due":[39],"to":[40,70],"inherent":[41],"variability":[42,59],"in":[43,60],"WSI":[44],"preparation":[45],"the":[47,61,96,103,128],"uncertain":[48],"condition":[49],"of":[50,65,99],"infected":[51],"tissues.":[52],"These":[53],"uncontrollable":[54],"external":[55],"factors":[56],"introduce":[57],"significant":[58],"numbers":[62],"resolutions":[64],"patients,":[68,135],"leading":[69],"bias":[71],"compromised":[73],"performance,":[74],"particularly":[75],"tail":[77,134],"with":[79,108,120],"limited":[80],"data.":[81],"In":[82],"this":[83],"paper,":[84],"we":[85],"propose":[86],"novel":[88,116],"approach,":[89],"PathoKD,":[90],"knowledge":[93,110,122],"distillation.":[94,123],"Recognizing":[95],"hierarchical":[97,121],"nature":[98],"disease":[100],"progression":[101],"data":[104],"scarcity":[105],"issues":[106],"associated":[107],"vanilla":[109],"distillation":[111],"methods,":[112],"PathoKD":[113],"integrates":[114],"curriculum":[117],"learning":[118],"framework":[119],"This":[124],"integration":[125],"effectively":[126],"mitigates":[127],"performance":[129],"gap":[130],"between":[131],"head":[132],"thereby":[136],"enhancing":[137],"accuracy":[139],"patient":[141],"groups.":[142],"Our":[143],"proposal":[144],"extensively":[146],"evaluated":[147],"over":[148],"popular":[149],"datasets":[150],"experimental":[152],"results":[153],"demonstrate":[154],"its":[155],"superiority.":[156]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
