{"id":"https://openalex.org/W2101896525","doi":"https://doi.org/10.1145/1065167.1065215","title":"Relative risk and odds ratio","display_name":"Relative risk and odds ratio","publication_year":2005,"publication_date":"2005-06-13","ids":{"openalex":"https://openalex.org/W2101896525","doi":"https://doi.org/10.1145/1065167.1065215","mag":"2101896525"},"language":"en","primary_location":{"id":"doi:10.1145/1065167.1065215","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1065167.1065215","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the twenty-fourth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems","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/A5066737474","display_name":"Haiquan Li","orcid":"https://orcid.org/0000-0002-8049-0278"},"institutions":[{"id":"https://openalex.org/I3005327000","display_name":"Institute for Infocomm Research","ror":"https://ror.org/053rfa017","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I3005327000","https://openalex.org/I91275662"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Haiquan Li","raw_affiliation_strings":["Institute for Infocomm Research, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Infocomm Research, Singapore","institution_ids":["https://openalex.org/I3005327000"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017861049","display_name":"Jinyan Li","orcid":"https://orcid.org/0000-0003-1833-7413"},"institutions":[{"id":"https://openalex.org/I3005327000","display_name":"Institute for Infocomm Research","ror":"https://ror.org/053rfa017","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I3005327000","https://openalex.org/I91275662"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Jinyan Li","raw_affiliation_strings":["Institute for Infocomm Research, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Infocomm Research, Singapore","institution_ids":["https://openalex.org/I3005327000"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012381970","display_name":"Limsoon Wong","orcid":"https://orcid.org/0000-0003-1241-5441"},"institutions":[{"id":"https://openalex.org/I3005327000","display_name":"Institute for Infocomm Research","ror":"https://ror.org/053rfa017","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I3005327000","https://openalex.org/I91275662"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Limsoon Wong","raw_affiliation_strings":["Institute for Infocomm Research, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Infocomm Research, Singapore","institution_ids":["https://openalex.org/I3005327000"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022222926","display_name":"Mengling Feng","orcid":"https://orcid.org/0000-0002-5338-6248"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Mengling Feng","raw_affiliation_strings":["Nanyang Technological University, Singapore","Nanyang Technological University (Singapore)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]},{"raw_affiliation_string":"Nanyang Technological University (Singapore)","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103379503","display_name":"Yap\u2010Peng Tan","orcid":"https://orcid.org/0000-0002-0645-9109"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Yap-Peng Tan","raw_affiliation_strings":["Nanyang Technological University, Singapore","Nanyang Technological University (Singapore)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]},{"raw_affiliation_string":"Nanyang Technological University (Singapore)","institution_ids":["https://openalex.org/I172675005"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.7509,"has_fulltext":false,"cited_by_count":65,"citation_normalized_percentile":{"value":0.91410198,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"368","last_page":"377"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.9937000274658203,"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/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9933000206947327,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/odds-ratio","display_name":"Odds ratio","score":0.7800711393356323},{"id":"https://openalex.org/keywords/odds","display_name":"Odds","score":0.7756857872009277},{"id":"https://openalex.org/keywords/convexity","display_name":"Convexity","score":0.6499149799346924},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6423077583312988},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.544043779373169},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5227980017662048},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.4432544410228729},{"id":"https://openalex.org/keywords/diagnostic-odds-ratio","display_name":"Diagnostic odds ratio","score":0.41216179728507996},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.32889413833618164},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3224349319934845},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.31827157735824585},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.29575681686401367},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2768512964248657},{"id":"https://openalex.org/keywords/confidence-interval","display_name":"Confidence interval","score":0.19337904453277588},{"id":"https://openalex.org/keywords/logistic-regression","display_name":"Logistic regression","score":0.09810394048690796},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.08662831783294678}],"concepts":[{"id":"https://openalex.org/C156957248","wikidata":"https://www.wikidata.org/wiki/Q1862216","display_name":"Odds ratio","level":2,"score":0.7800711393356323},{"id":"https://openalex.org/C143095724","wikidata":"https://www.wikidata.org/wiki/Q515895","display_name":"Odds","level":3,"score":0.7756857872009277},{"id":"https://openalex.org/C72134830","wikidata":"https://www.wikidata.org/wiki/Q5166524","display_name":"Convexity","level":2,"score":0.6499149799346924},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6423077583312988},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.544043779373169},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5227980017662048},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.4432544410228729},{"id":"https://openalex.org/C157481446","wikidata":"https://www.wikidata.org/wiki/Q5270351","display_name":"Diagnostic odds ratio","level":3,"score":0.41216179728507996},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32889413833618164},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3224349319934845},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.31827157735824585},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.29575681686401367},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2768512964248657},{"id":"https://openalex.org/C44249647","wikidata":"https://www.wikidata.org/wiki/Q208498","display_name":"Confidence interval","level":2,"score":0.19337904453277588},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.09810394048690796},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.08662831783294678},{"id":"https://openalex.org/C106159729","wikidata":"https://www.wikidata.org/wiki/Q2294553","display_name":"Financial economics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/1065167.1065215","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1065167.1065215","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the twenty-fourth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems","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":26,"referenced_works":["https://openalex.org/W43825479","https://openalex.org/W110175884","https://openalex.org/W159524162","https://openalex.org/W205241832","https://openalex.org/W1483730712","https://openalex.org/W1493790738","https://openalex.org/W1516756414","https://openalex.org/W1536736992","https://openalex.org/W1537336823","https://openalex.org/W1581597260","https://openalex.org/W1585646276","https://openalex.org/W1973036367","https://openalex.org/W1977591786","https://openalex.org/W2038812321","https://openalex.org/W2064853889","https://openalex.org/W2066277072","https://openalex.org/W2066771339","https://openalex.org/W2118843309","https://openalex.org/W2129555316","https://openalex.org/W2141115288","https://openalex.org/W2162034534","https://openalex.org/W2166559705","https://openalex.org/W2224601850","https://openalex.org/W2337480916","https://openalex.org/W4252403066","https://openalex.org/W6629461242"],"related_works":["https://openalex.org/W4315650970","https://openalex.org/W1999597698","https://openalex.org/W2118847041","https://openalex.org/W2024025088","https://openalex.org/W2016483411","https://openalex.org/W2403534611","https://openalex.org/W2167134322","https://openalex.org/W2419315711","https://openalex.org/W2136790891","https://openalex.org/W2121514893"],"abstract_inverted_index":{"We":[0,164,211,215],"are":[1,26,31,244],"often":[2],"interested":[3],"to":[4,35,117,123,195,227,236],"test":[5],"whether":[6],"a":[7,11,112,118,127,188,233],"given":[8,12],"cause":[9],"has":[10,74,114,130,147],"effect.":[13],"If":[14],"we":[15,160,186],"cannot":[16],"specify":[17],"the":[18,21,58,63,71,75,81,85,88,99,104,124,153,197,201,219],"nature":[19],"of":[20,53,65,70,95,106,137,176,190,204,238],"factors":[22,40],"involved,":[23],"such":[24,162,205],"tests":[25],"called":[27],"model-free":[28],"studies.":[29],"There":[30],"two":[32],"major":[33],"strategies":[34],"demonstrate":[36,217],"associations":[37],"between":[38],"risk":[39,119,143],"(ie.":[41,46,73,79,87],"patterns)":[42],"and":[43,57,98,192,200],"outcome":[44],"phenotypes":[45],"class":[47,89],"labels).":[48],"The":[49,91,109,134],"first":[50],"is":[51,60,93,101,121,225],"that":[52,94,111,129,139,166,218,237,246],"prospective":[54],"study":[55],"designs,":[56,97],"analysis":[59,100],"based":[61,102,179],"on":[62,103,180],"concept":[64,105],"\"relative":[66],"risk\":":[67],"What":[68],"fraction":[69],"exposed":[72,116],"pattern)":[76,82],"or":[77],"unexposed":[78],"lacks":[80],"individuals":[83],"have":[84,140],"phenotype":[86],"label)?":[90],"second":[92],"retrospective":[96],"\"odds":[107],"ratio\":":[108],"odds":[110,125,145],"case":[113,128],"been":[115,132,149],"factor":[120],"compared":[122],"for":[126],"not":[131,148],"exposed.":[133],"efficient":[135,221],"extraction":[136],"patterns":[138,206,231,245],"good":[141],"relative":[142],"and/or":[144],"ratio":[146],"previously":[150],"studied":[151],"in":[152],"data":[154],"mining":[155,239],"context.":[156],"In":[157],"this":[158,167],"paper,":[159],"investigate":[161],"patterns.":[163],"show":[165],"pattern":[168],"space":[169],"can":[170],"be":[171],"systematically":[172],"stratified":[173],"into":[174],"plateaus":[175],"convex":[177],"spaces":[178],"their":[181],"support":[182,209],"levels.":[183],"Exploiting":[184],"convexity,":[185],"formulate":[187],"number":[189],"sound":[191],"complete":[193],"algorithms":[194,224],"extract":[196],"most":[198,202,220],"general":[199],"specific":[203],"at":[207,232],"each":[208],"level.":[210],"compare":[212],"these":[213,223,229],"algorithms.":[214],"further":[216],"among":[222],"able":[226],"mine":[228],"sophisticated":[230],"speed":[234],"comparable":[235],"frequent":[240],"closed":[241],"patterns,":[242],"which":[243],"satisfy":[247],"considerably":[248],"simpler":[249],"conditions.":[250]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":4},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":6}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
