{"id":"https://openalex.org/W2107098692","doi":"https://doi.org/10.1145/1835804.1835830","title":"An integrated machine learning approach to stroke prediction","display_name":"An integrated machine learning approach to stroke prediction","publication_year":2010,"publication_date":"2010-07-25","ids":{"openalex":"https://openalex.org/W2107098692","doi":"https://doi.org/10.1145/1835804.1835830","mag":"2107098692"},"language":"en","primary_location":{"id":"doi:10.1145/1835804.1835830","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1835804.1835830","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining","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/A5104110845","display_name":"Aditya Khosla","orcid":null},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Aditya Khosla","raw_affiliation_strings":["Stanford University, Stanford, USA","Stanford University, Stanford , USA"],"affiliations":[{"raw_affiliation_string":"Stanford University, Stanford, USA","institution_ids":["https://openalex.org/I97018004"]},{"raw_affiliation_string":"Stanford University, Stanford , USA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040974245","display_name":"Yu Cao","orcid":"https://orcid.org/0000-0002-1965-5854"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yu Cao","raw_affiliation_strings":["Stanford University, Stanford, USA","Stanford University, Stanford , USA"],"affiliations":[{"raw_affiliation_string":"Stanford University, Stanford, USA","institution_ids":["https://openalex.org/I97018004"]},{"raw_affiliation_string":"Stanford University, Stanford , USA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035984937","display_name":"Cliff Chiung-Yu Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Cliff Chiung-Yu Lin","raw_affiliation_strings":["Stanford University, Stanford, USA","Stanford University, Stanford , USA"],"affiliations":[{"raw_affiliation_string":"Stanford University, Stanford, USA","institution_ids":["https://openalex.org/I97018004"]},{"raw_affiliation_string":"Stanford University, Stanford , USA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063291957","display_name":"Hsu-kuang Chiu","orcid":"https://orcid.org/0000-0002-8643-017X"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hsu-Kuang Chiu","raw_affiliation_strings":["Stanford University, Stanford, USA","Stanford University, Stanford , USA"],"affiliations":[{"raw_affiliation_string":"Stanford University, Stanford, USA","institution_ids":["https://openalex.org/I97018004"]},{"raw_affiliation_string":"Stanford University, Stanford , USA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103937904","display_name":"Junling Hu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210150719","display_name":"eBay (United States)","ror":"https://ror.org/05cnabr44","country_code":"US","type":"company","lineage":["https://openalex.org/I4210150719"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Junling Hu","raw_affiliation_strings":["eBay Inc, San Jose, USA","EBay Inc., San Jose, USA"],"affiliations":[{"raw_affiliation_string":"eBay Inc, San Jose, USA","institution_ids":["https://openalex.org/I4210150719"]},{"raw_affiliation_string":"EBay Inc., San Jose, USA","institution_ids":["https://openalex.org/I4210150719"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108652283","display_name":"Honglak Lee","orcid":"https://orcid.org/0000-0002-1279-0068"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Honglak Lee","raw_affiliation_strings":["Stanford University, Stanford, USA","Stanford University, Stanford , USA"],"affiliations":[{"raw_affiliation_string":"Stanford University, Stanford, USA","institution_ids":["https://openalex.org/I97018004"]},{"raw_affiliation_string":"Stanford University, Stanford , USA","institution_ids":["https://openalex.org/I97018004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5104110845"],"corresponding_institution_ids":["https://openalex.org/I97018004"],"apc_list":null,"apc_paid":null,"fwci":1.5198,"has_fulltext":false,"cited_by_count":200,"citation_normalized_percentile":{"value":0.82995211,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"183","last_page":"192"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10227","display_name":"Acute Ischemic Stroke Management","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10227","display_name":"Acute Ischemic Stroke Management","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"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/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.98089998960495,"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"}},{"id":"https://openalex.org/T14374","display_name":"Statistical Methods in Epidemiology","score":0.9634000062942505,"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/feature-selection","display_name":"Feature selection","score":0.7478944063186646},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6570484042167664},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6539895534515381},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5971342325210571},{"id":"https://openalex.org/keywords/proportional-hazards-model","display_name":"Proportional hazards model","score":0.589135468006134},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5869550108909607},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.5753659605979919},{"id":"https://openalex.org/keywords/imputation","display_name":"Imputation (statistics)","score":0.5196093916893005},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4693528115749359},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3903101682662964},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.2840239405632019},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.22564783692359924},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1252615749835968}],"concepts":[{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.7478944063186646},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6570484042167664},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6539895534515381},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5971342325210571},{"id":"https://openalex.org/C50382708","wikidata":"https://www.wikidata.org/wiki/Q223218","display_name":"Proportional hazards model","level":2,"score":0.589135468006134},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5869550108909607},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.5753659605979919},{"id":"https://openalex.org/C58041806","wikidata":"https://www.wikidata.org/wiki/Q1660484","display_name":"Imputation (statistics)","level":3,"score":0.5196093916893005},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4693528115749359},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3903101682662964},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.2840239405632019},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.22564783692359924},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1252615749835968}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/1835804.1835830","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1835804.1835830","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.225.3401","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.225.3401","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.eecs.umich.edu/%7Ehonglak/kdd10-strokeprediction.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320313176","display_name":"Robert Bosch","ror":"https://ror.org/02venad53"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W3219084","https://openalex.org/W40769662","https://openalex.org/W53188351","https://openalex.org/W1504194272","https://openalex.org/W1592785605","https://openalex.org/W1922017469","https://openalex.org/W1978358980","https://openalex.org/W1990464273","https://openalex.org/W2004915807","https://openalex.org/W2008515369","https://openalex.org/W2009787800","https://openalex.org/W2021733365","https://openalex.org/W2037406584","https://openalex.org/W2070771761","https://openalex.org/W2081988817","https://openalex.org/W2083384274","https://openalex.org/W2084855690","https://openalex.org/W2101095383","https://openalex.org/W2102194577","https://openalex.org/W2111700774","https://openalex.org/W2113642685","https://openalex.org/W2115709314","https://openalex.org/W2117807566","https://openalex.org/W2120100126","https://openalex.org/W2125782079","https://openalex.org/W2135046866","https://openalex.org/W2135723633","https://openalex.org/W2136916987","https://openalex.org/W2144755725","https://openalex.org/W2157825442","https://openalex.org/W2160842550","https://openalex.org/W2161197885","https://openalex.org/W2174160981","https://openalex.org/W2314052258","https://openalex.org/W2334038090","https://openalex.org/W2370671790","https://openalex.org/W2406624004","https://openalex.org/W2768019923","https://openalex.org/W2990138404","https://openalex.org/W2998216295","https://openalex.org/W3175417087","https://openalex.org/W4214512856","https://openalex.org/W4285719527","https://openalex.org/W4401149187"],"related_works":["https://openalex.org/W3125011624","https://openalex.org/W1508631387","https://openalex.org/W2370917603","https://openalex.org/W2952760143","https://openalex.org/W2017776670","https://openalex.org/W4211215373","https://openalex.org/W3217094455","https://openalex.org/W2347897961","https://openalex.org/W2340870721","https://openalex.org/W2379140333"],"abstract_inverted_index":{"Stroke":[0],"is":[1,24],"the":[2,9,17,37,51,60,108,115,137,152,159],"third":[3],"leading":[4],"cause":[5,11],"of":[6,12,22,63,139,165,196],"death":[7],"and":[8,30,68,120,167,204],"principal":[10],"serious":[13],"long-term":[14],"disability":[15],"in":[16,70,162],"United":[18],"States.":[19],"Accurate":[20],"prediction":[21,49,69,195],"stroke":[23,48],"highly":[25],"valuable":[26],"for":[27,47],"early":[28],"intervention":[29],"treatment.":[31],"In":[32,170],"this":[33],"study,":[34],"we":[35,58,128],"compare":[36],"Cox":[38,116,123,153],"proportional":[39,117],"hazards":[40,118],"model":[41,119],"with":[42,93,142],"a":[43,75,104,130,147],"machine":[44],"learning":[45],"approach":[46,157],"on":[50,86],"Cardiovascular":[52],"Health":[53],"Study":[54],"(CHS)":[55],"dataset.":[56],"Specifically,":[57],"consider":[59],"common":[61,203],"problems":[62],"data":[64,201],"imputation,":[65],"feature":[66,78,100,124],"selection,":[67],"medical":[71],"datasets.":[72],"We":[73],"propose":[74],"novel":[76],"automatic":[77],"selection":[79,101,125],"algorithm":[80,102,134],"that":[81,135,180],"selects":[82],"robust":[83],"features":[84],"based":[85],"our":[87,98,156,172],"proposed":[88,99],"heuristic:":[89],"conservative":[90],"mean.":[91],"Combined":[92],"Support":[94],"Vector":[95],"Machines":[96],"(SVMs),":[97],"achieves":[103],"greater":[105],"area":[106],"under":[107],"ROC":[109],"curve":[110],"(AUC)":[111],"as":[112],"compared":[113],"to":[114,145,193],"L1":[121],"regularized":[122],"algorithm.":[126],"Furthermore,":[127],"present":[129],"margin-based":[131,140],"censored":[132,143],"regression":[133,144],"combines":[136],"concept":[138],"classifiers":[141],"achieve":[146],"better":[148],"concordance":[149,168],"index":[150],"than":[151],"model.":[154],"Overall,":[155],"outperforms":[158],"current":[160],"state-of-the-art":[161],"both":[163],"metrics":[164],"AUC":[166],"index.":[169],"addition,":[171],"work":[173],"has":[174],"also":[175],"identified":[176],"potential":[177],"risk":[178,205],"factors":[179,206],"have":[181],"not":[182,208],"been":[183],"discovered":[184],"by":[185],"traditional":[186],"approaches.":[187],"Our":[188],"method":[189],"can":[190],"be":[191],"applied":[192],"clinical":[194],"other":[197],"diseases,":[198],"where":[199],"missing":[200],"are":[202,207],"well":[209],"understood.":[210]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":26},{"year":2024,"cited_by_count":23},{"year":2023,"cited_by_count":28},{"year":2022,"cited_by_count":20},{"year":2021,"cited_by_count":28},{"year":2020,"cited_by_count":14},{"year":2019,"cited_by_count":10},{"year":2018,"cited_by_count":13},{"year":2017,"cited_by_count":10},{"year":2016,"cited_by_count":12},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":4},{"year":2012,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
