{"id":"https://openalex.org/W2048386500","doi":"https://doi.org/10.4018/jkdb.2011070104","title":"Medical Survival Analysis Through Transduction of Semi-Supervised Regression Targets","display_name":"Medical Survival Analysis Through Transduction of Semi-Supervised Regression Targets","publication_year":2011,"publication_date":"2011-07-01","ids":{"openalex":"https://openalex.org/W2048386500","doi":"https://doi.org/10.4018/jkdb.2011070104","mag":"2048386500"},"language":"en","primary_location":{"id":"doi:10.4018/jkdb.2011070104","is_oa":false,"landing_page_url":"https://doi.org/10.4018/jkdb.2011070104","pdf_url":null,"source":{"id":"https://openalex.org/S113982356","display_name":"International Journal of Knowledge Discovery in Bioinformatics","issn_l":"1947-9115","issn":["1947-9115","1947-9123"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320424","host_organization_name":"IGI Global","host_organization_lineage":["https://openalex.org/P4310320424"],"host_organization_lineage_names":["IGI Global"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Knowledge Discovery in Bioinformatics","raw_type":"journal-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/A5016894767","display_name":"Faisal M. Khan","orcid":"https://orcid.org/0000-0002-5116-7471"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Faisal M. Khan","raw_affiliation_strings":["Rutgers University, USA","Rutgers University, , USA"],"affiliations":[{"raw_affiliation_string":"Rutgers University, USA","institution_ids":["https://openalex.org/I102322142"]},{"raw_affiliation_string":"Rutgers University, , USA","institution_ids":["https://openalex.org/I102322142"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076513019","display_name":"Qiuhua Liu","orcid":"https://orcid.org/0000-0001-7476-4634"},"institutions":[{"id":"https://openalex.org/I4210090857","display_name":"Schlumberger (United States)","ror":"https://ror.org/009m79n22","country_code":"US","type":"company","lineage":["https://openalex.org/I4210090857","https://openalex.org/I4210092184"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qiuhua Liu","raw_affiliation_strings":["Schlumberger Limited, USA"],"affiliations":[{"raw_affiliation_string":"Schlumberger Limited, USA","institution_ids":["https://openalex.org/I4210090857"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5016894767"],"corresponding_institution_ids":["https://openalex.org/I102322142"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.1152419,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"2","issue":"3","first_page":"52","last_page":"65"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9966999888420105,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9966999888420105,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10885","display_name":"Gene expression and cancer classification","score":0.9839000105857849,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9714999794960022,"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/regression","display_name":"Regression","score":0.717531144618988},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.6202096939086914},{"id":"https://openalex.org/keywords/survival-analysis","display_name":"Survival analysis","score":0.5855404734611511},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5854997634887695},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5513203740119934},{"id":"https://openalex.org/keywords/transduction","display_name":"Transduction (biophysics)","score":0.4497881531715393},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4393458664417267},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.43882936239242554},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.42713814973831177},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21504619717597961},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.16457796096801758},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.09040406346321106}],"concepts":[{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.717531144618988},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.6202096939086914},{"id":"https://openalex.org/C10515644","wikidata":"https://www.wikidata.org/wiki/Q543310","display_name":"Survival analysis","level":2,"score":0.5855404734611511},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5854997634887695},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5513203740119934},{"id":"https://openalex.org/C15152581","wikidata":"https://www.wikidata.org/wiki/Q7833966","display_name":"Transduction (biophysics)","level":2,"score":0.4497881531715393},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4393458664417267},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.43882936239242554},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.42713814973831177},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21504619717597961},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.16457796096801758},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.09040406346321106},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.4018/jkdb.2011070104","is_oa":false,"landing_page_url":"https://doi.org/10.4018/jkdb.2011070104","pdf_url":null,"source":{"id":"https://openalex.org/S113982356","display_name":"International Journal of Knowledge Discovery in Bioinformatics","issn_l":"1947-9115","issn":["1947-9115","1947-9123"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320424","host_organization_name":"IGI Global","host_organization_lineage":["https://openalex.org/P4310320424"],"host_organization_lineage_names":["IGI Global"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Knowledge Discovery in Bioinformatics","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:igg:jkdb00:v:2:y:2011:i:3:p:52-65","is_oa":false,"landing_page_url":"http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/jkdb.2011070104","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.4699999988079071}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W57680428","https://openalex.org/W150987698","https://openalex.org/W1546313835","https://openalex.org/W1972404374","https://openalex.org/W1980485115","https://openalex.org/W1997029057","https://openalex.org/W2018116321","https://openalex.org/W2048440423","https://openalex.org/W2058614027","https://openalex.org/W2070216889","https://openalex.org/W2075818274","https://openalex.org/W2104290444","https://openalex.org/W2107968230","https://openalex.org/W2108268158","https://openalex.org/W2109269939","https://openalex.org/W2120605054","https://openalex.org/W2121234459","https://openalex.org/W2122565017","https://openalex.org/W2122837498","https://openalex.org/W2125527920","https://openalex.org/W2125782079","https://openalex.org/W2128718068","https://openalex.org/W2139212933","https://openalex.org/W2144603192","https://openalex.org/W2148603752","https://openalex.org/W2149753464","https://openalex.org/W2170938446","https://openalex.org/W2519641626","https://openalex.org/W2964057329","https://openalex.org/W2997701990","https://openalex.org/W3144619878","https://openalex.org/W3147894994","https://openalex.org/W3175417087","https://openalex.org/W4285719527","https://openalex.org/W4384306321","https://openalex.org/W6602375370","https://openalex.org/W6679517787"],"related_works":["https://openalex.org/W4289356671","https://openalex.org/W2389155397","https://openalex.org/W2165884543","https://openalex.org/W2312753042","https://openalex.org/W3186837933","https://openalex.org/W2368989808","https://openalex.org/W2034959125","https://openalex.org/W2355687852","https://openalex.org/W3174513558","https://openalex.org/W2114200869"],"abstract_inverted_index":{"A":[0],"crucial":[1],"challenge":[2],"in":[3,20,87,179,184],"predictive":[4,157],"modeling":[5],"for":[6,141,155],"survival":[7,142,152,172],"analysis":[8,153,173],"applications":[9,167],"such":[10,45],"as":[11,80,104],"medical":[12],"prognosis":[13,189],"is":[14,59,61],"the":[15,21,38,42,47,70,83,95,119,126,165,182],"accounting":[16],"of":[17,41,51,54,98,164,168],"censored":[18,39,63,75,127],"observations":[19],"data.":[22,43],"While":[23,74],"these":[24],"time-to-event":[25],"predictions":[26],"inherently":[27],"represent":[28],"a":[29,52,62,113,176],"regression":[30,33,89,139,170],"problem,":[31],"traditional":[32,138],"approaches":[34],"are":[35,56,102,123],"challenged":[36],"by":[37],"characteristics":[40],"In":[44],"problems":[46],"true":[48,71,120],"target":[49,64,72,121],"times":[50,122,128],"majority":[53],"instances":[55],"unknown;":[57],"what":[58],"known":[60],"representing":[65],"some":[66],"indeterminate":[67],"time":[68],"before":[69],"time.":[73],"samples":[76,101],"can":[77,133,145],"be":[78,134,146],"considered":[79],"semi-supervised":[81,88,115,169],"targets,":[82],"current":[84],"limited":[85],"efforts":[86],"do":[90],"not":[91],"take":[92],"into":[93],"account":[94],"partial":[96],"nature":[97],"unsupervised":[99],"information;":[100],"treated":[103],"either":[105],"fully":[106],"labeled":[107],"or":[108,144],"unlabelled.":[109],"This":[110],"paper":[111],"presents":[112],"novel":[114],"learning":[116],"approach":[117,161],"where":[118],"approximated":[124],"from":[125],"through":[129],"transduction.":[130],"The":[131,159],"method":[132],"employed":[135,147],"to":[136,148,171],"transform":[137],"methods":[140,154],"analysis,":[143],"enhance":[149],"existing":[150],"state-of-the-art":[151,183],"improved":[156],"performance.":[158],"proposed":[160],"represents":[162],"one":[163],"first":[166],"and":[174,186],"yields":[175],"significant":[177],"improvement":[178],"performance":[180],"over":[181],"prostate":[185],"breast":[187],"cancer":[188],"applications.":[190]},"counts_by_year":[{"year":2018,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
