{"id":"https://openalex.org/W2147838747","doi":"https://doi.org/10.1145/2661829.2662065","title":"Active Learning based Survival Regression for Censored Data","display_name":"Active Learning based Survival Regression for Censored Data","publication_year":2014,"publication_date":"2014-11-03","ids":{"openalex":"https://openalex.org/W2147838747","doi":"https://doi.org/10.1145/2661829.2662065","mag":"2147838747"},"language":"en","primary_location":{"id":"doi:10.1145/2661829.2662065","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2661829.2662065","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"type":"conference-paper","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/A5017540117","display_name":"Bhanukiran Vinzamuri","orcid":"https://orcid.org/0000-0003-2651-8628"},"institutions":[{"id":"https://openalex.org/I185443292","display_name":"Wayne State University","ror":"https://ror.org/01070mq45","country_code":"US","type":"education","lineage":["https://openalex.org/I185443292"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bhanukiran Vinzamuri","raw_affiliation_strings":["Wayne State University, Detroit, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wayne State University, Detroit, USA","institution_ids":["https://openalex.org/I185443292"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101766443","display_name":"Yan Li","orcid":"https://orcid.org/0000-0002-1249-9326"},"institutions":[{"id":"https://openalex.org/I185443292","display_name":"Wayne State University","ror":"https://ror.org/01070mq45","country_code":"US","type":"education","lineage":["https://openalex.org/I185443292"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yan Li","raw_affiliation_strings":["Wayne State University, Detroit, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wayne State University, Detroit, USA","institution_ids":["https://openalex.org/I185443292"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001022750","display_name":"Chandan K. Reddy","orcid":"https://orcid.org/0000-0003-2839-3662"},"institutions":[{"id":"https://openalex.org/I185443292","display_name":"Wayne State University","ror":"https://ror.org/01070mq45","country_code":"US","type":"education","lineage":["https://openalex.org/I185443292"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chandan K. Reddy","raw_affiliation_strings":["Wayne State University, Detroit, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wayne State University, Detroit, USA","institution_ids":["https://openalex.org/I185443292"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I185443292"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":51,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"241","last_page":"250"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9980000257492065,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9980000257492065,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.9962999820709229,"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/T10136","display_name":"Statistical Methods and Inference","score":0.9898999929428101,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7398936152458191},{"id":"https://openalex.org/keywords/censoring","display_name":"Censoring (clinical trials)","score":0.7208592295646667},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6610814929008484},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.588570237159729},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5628578066825867},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.54731684923172},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.5027153491973877},{"id":"https://openalex.org/keywords/censored-regression-model","display_name":"Censored regression model","score":0.49510541558265686},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.4310232698917389},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4178258180618286},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2631074786186218},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12227845191955566}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7398936152458191},{"id":"https://openalex.org/C137668524","wikidata":"https://www.wikidata.org/wiki/Q189813","display_name":"Censoring (clinical trials)","level":2,"score":0.7208592295646667},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6610814929008484},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.588570237159729},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5628578066825867},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.54731684923172},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.5027153491973877},{"id":"https://openalex.org/C97379794","wikidata":"https://www.wikidata.org/wiki/Q4503892","display_name":"Censored regression model","level":3,"score":0.49510541558265686},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.4310232698917389},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4178258180618286},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2631074786186218},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12227845191955566},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2661829.2662065","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2661829.2662065","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.75,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G6759206228","display_name":null,"funder_award_id":"IIS-1231742","funder_id":"https://openalex.org/F4320337389","funder_display_name":"Division of Information and Intelligent Systems"},{"id":"https://openalex.org/G7264614435","display_name":null,"funder_award_id":"IIS-1242304","funder_id":"https://openalex.org/F4320337389","funder_display_name":"Division of Information and Intelligent Systems"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320337389","display_name":"Division of Information and Intelligent Systems","ror":"https://ror.org/053a2cp42"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1580788756","https://openalex.org/W1966455406","https://openalex.org/W1972987731","https://openalex.org/W1978575887","https://openalex.org/W1996712239","https://openalex.org/W2011745127","https://openalex.org/W2011995986","https://openalex.org/W2021367230","https://openalex.org/W2026706435","https://openalex.org/W2039006773","https://openalex.org/W2039284087","https://openalex.org/W2041638842","https://openalex.org/W2043681863","https://openalex.org/W2052825782","https://openalex.org/W2065189618","https://openalex.org/W2086923543","https://openalex.org/W2099620796","https://openalex.org/W2108268158","https://openalex.org/W2117927740","https://openalex.org/W2125782079","https://openalex.org/W2135793597","https://openalex.org/W2144603192","https://openalex.org/W2149199519","https://openalex.org/W2153789527","https://openalex.org/W2157076315","https://openalex.org/W2160828669","https://openalex.org/W2160842550","https://openalex.org/W2331273242","https://openalex.org/W2570764145","https://openalex.org/W2798135227","https://openalex.org/W2903158431","https://openalex.org/W2990138404","https://openalex.org/W3099478002","https://openalex.org/W4214512856","https://openalex.org/W4226182047","https://openalex.org/W4285719527","https://openalex.org/W6634508654","https://openalex.org/W6661048866","https://openalex.org/W6756615331","https://openalex.org/W7073710283"],"related_works":["https://openalex.org/W2100281361","https://openalex.org/W4243328373","https://openalex.org/W1546133898","https://openalex.org/W1500747244","https://openalex.org/W2061517165","https://openalex.org/W1882017865","https://openalex.org/W31220157","https://openalex.org/W2312753042","https://openalex.org/W4289356671","https://openalex.org/W2389155397"],"abstract_inverted_index":{"Time-to-event":[0],"outcomes":[1,15],"based":[2,128,138],"data":[3,19,75],"can":[4,12,80,108],"be":[5],"modelled":[6],"using":[7,76],"survival":[8,77,129,152,167],"regression":[9,48,78,168],"methods":[10,61,79,169],"which":[11,43,131,194],"predict":[13],"these":[14],"in":[16,21,40,100,189,199],"different":[17],"censored":[18,38,69,74,155],"applications":[20],"diverse":[22],"fields":[23],"such":[24],"as":[25,53],"engineering,":[26],"economics":[27],"and":[28,58,153],"healthcare.":[29],"Predictive":[30],"models":[31],"are":[32],"built":[33],"by":[34,123],"inferring":[35],"from":[36,46,73],"the":[37,68,82,89,93,101,111,165,171,176,182,186],"variable":[39,57],"time-to-event":[41,90],"data,":[42],"differentiates":[44],"them":[45],"other":[47,202],"methods.":[49],"Censoring":[50],"is":[51],"represented":[52],"a":[54,85,105,133],"binary":[55],"indicator":[56],"machine":[59],"learning":[60,72,127,192,197],"have":[62],"been":[63],"tuned":[64],"to":[65,201],"account":[66],"for":[67,88,185],"attribute.":[70],"Active":[71],"make":[81],"model":[83,112,130,135],"query":[84],"domain":[86,103,106],"expert":[87,107],"label":[91],"of":[92,157,164,175],"sampled":[94],"instances.":[95],"This":[96],"offers":[97],"higher":[98,172],"advantages":[99],"healthcare":[102],"where":[104],"interactively":[109],"refine":[110],"with":[113],"his":[114],"feedback.":[115],"With":[116],"this":[117,121,143],"motivation,":[118],"we":[119],"address":[120],"problem":[122],"providing":[124],"an":[125,190],"active":[126,191],"uses":[132],"novel":[134],"discriminative":[136,173],"gradient":[137],"sampling":[139,183,203],"scheme.":[140],"We":[141,179],"evaluate":[142],"framework":[144],"on":[145],"electronic":[146],"health":[147],"records":[148],"(EHR),":[149],"publicly":[150],"available":[151],"synthetic":[154],"datasets":[156],"varying":[158],"diversity.":[159],"Experimental":[160],"evaluation":[161],"against":[162],"state":[163],"art":[166],"indicates":[170],"ability":[174],"proposed":[177,187],"approach.":[178],"also":[180],"present":[181],"results":[184],"approach":[188],"setting":[193],"indicate":[195],"better":[196],"rates":[198],"comparison":[200],"strategies.":[204]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":7},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":5},{"year":2016,"cited_by_count":10},{"year":2015,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}