{"id":"https://openalex.org/W2469019492","doi":"https://doi.org/10.1109/tcbb.2016.2591539","title":"Prognosis of Clinical Outcomes with Temporal Patterns and Experiences with One Class Feature Selection","display_name":"Prognosis of Clinical Outcomes with Temporal Patterns and Experiences with One Class Feature Selection","publication_year":2016,"publication_date":"2016-07-14","ids":{"openalex":"https://openalex.org/W2469019492","doi":"https://doi.org/10.1109/tcbb.2016.2591539","mag":"2469019492","pmid":"https://pubmed.ncbi.nlm.nih.gov/27429447"},"language":"en","primary_location":{"id":"doi:10.1109/tcbb.2016.2591539","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcbb.2016.2591539","pdf_url":null,"source":{"id":"https://openalex.org/S36029991","display_name":"IEEE/ACM Transactions on Computational Biology and Bioinformatics","issn_l":"1545-5963","issn":["1545-5963","1557-9964","2374-0043"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE/ACM Transactions on Computational Biology and Bioinformatics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/5486920","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5048791149","display_name":"Robert Moskovitch","orcid":"https://orcid.org/0000-0002-2138-5080"},"institutions":[{"id":"https://openalex.org/I124227911","display_name":"Ben-Gurion University of the Negev","ror":"https://ror.org/05tkyf982","country_code":"IL","type":"education","lineage":["https://openalex.org/I124227911"]},{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["IL","US"],"is_corresponding":false,"raw_author_name":"Robert Moskovitch","raw_affiliation_strings":["Department of Software and Information Systems EngineeringBen Gurion University","Biomedical Informatics, Columbia University, New York, NY","Department of Software and Information Systems Engineering, Ben Gurion University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Software and Information Systems EngineeringBen Gurion University","institution_ids":[]},{"raw_affiliation_string":"Biomedical Informatics, Columbia University, New York, NY","institution_ids":["https://openalex.org/I78577930"]},{"raw_affiliation_string":"Department of Software and Information Systems Engineering, Ben Gurion University","institution_ids":["https://openalex.org/I124227911"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056721281","display_name":"Hyunmi Choi","orcid":"https://orcid.org/0000-0002-0826-2350"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hyunmi Choi","raw_affiliation_strings":["Department of Neurology, Columbia University, New York, NY"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Neurology, Columbia University, New York, NY","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053670656","display_name":"George Hripcsak","orcid":"https://orcid.org/0000-0003-2664-7614"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"George Hripcsak","raw_affiliation_strings":["Department of Biomedical Inforamtics, Columbia University, New York, NY"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biomedical Inforamtics, Columbia University, New York, NY","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086753691","display_name":"Nicholas P. Tatonetti","orcid":"https://orcid.org/0000-0002-2700-2597"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nicholas P. Tatonetti","raw_affiliation_strings":["Department of Biomedical Inforamtics, Systems Biology, and Medicine, Columbia University, New York, NY"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biomedical Inforamtics, Systems Biology, and Medicine, Columbia University, New York, NY","institution_ids":["https://openalex.org/I78577930"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.0009,"has_fulltext":false,"cited_by_count":37,"citation_normalized_percentile":{"value":0.92159942,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"14","issue":"3","first_page":"555","last_page":"563"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.9976999759674072,"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/T11309","display_name":"Music and Audio Processing","score":0.9940999746322632,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/feature-selection","display_name":"Feature selection","score":0.6584211587905884},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.627216100692749},{"id":"https://openalex.org/keywords/abstraction","display_name":"Abstraction","score":0.58275306224823},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5783476829528809},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5769267678260803},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5728175044059753},{"id":"https://openalex.org/keywords/outcome","display_name":"Outcome (game theory)","score":0.554157555103302},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5274560451507568},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5049434304237366},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.48685067892074585},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.43968838453292847},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40848782658576965},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1437520682811737}],"concepts":[{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6584211587905884},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.627216100692749},{"id":"https://openalex.org/C124304363","wikidata":"https://www.wikidata.org/wiki/Q673661","display_name":"Abstraction","level":2,"score":0.58275306224823},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5783476829528809},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5769267678260803},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5728175044059753},{"id":"https://openalex.org/C148220186","wikidata":"https://www.wikidata.org/wiki/Q7111912","display_name":"Outcome (game theory)","level":2,"score":0.554157555103302},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5274560451507568},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5049434304237366},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48685067892074585},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.43968838453292847},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40848782658576965},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1437520682811737},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C144237770","wikidata":"https://www.wikidata.org/wiki/Q747534","display_name":"Mathematical economics","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008490","descriptor_name":"Medical Informatics","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D008490","descriptor_name":"Medical Informatics","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D008490","descriptor_name":"Medical Informatics","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D008490","descriptor_name":"Medical Informatics","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D011379","descriptor_name":"Prognosis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D011379","descriptor_name":"Prognosis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D011379","descriptor_name":"Prognosis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D011379","descriptor_name":"Prognosis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D013997","descriptor_name":"Time Factors","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D013997","descriptor_name":"Time Factors","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D013997","descriptor_name":"Time Factors","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D013997","descriptor_name":"Time Factors","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016896","descriptor_name":"Treatment Outcome","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016896","descriptor_name":"Treatment Outcome","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016896","descriptor_name":"Treatment Outcome","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016896","descriptor_name":"Treatment Outcome","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D057225","descriptor_name":"Data Mining","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D057225","descriptor_name":"Data Mining","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D057225","descriptor_name":"Data Mining","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D057225","descriptor_name":"Data Mining","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D057286","descriptor_name":"Electronic Health Records","qualifier_ui":"Q000145","qualifier_name":"classification","is_major_topic":false},{"descriptor_ui":"D057286","descriptor_name":"Electronic Health Records","qualifier_ui":"Q000145","qualifier_name":"classification","is_major_topic":false},{"descriptor_ui":"D057286","descriptor_name":"Electronic Health Records","qualifier_ui":"Q000145","qualifier_name":"classification","is_major_topic":false},{"descriptor_ui":"D057286","descriptor_name":"Electronic Health Records","qualifier_ui":"Q000145","qualifier_name":"classification","is_major_topic":false}],"locations_count":4,"locations":[{"id":"doi:10.1109/tcbb.2016.2591539","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcbb.2016.2591539","pdf_url":null,"source":{"id":"https://openalex.org/S36029991","display_name":"IEEE/ACM Transactions on Computational Biology and Bioinformatics","issn_l":"1545-5963","issn":["1545-5963","1557-9964","2374-0043"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE/ACM Transactions on Computational Biology and Bioinformatics","raw_type":"journal-article"},{"id":"pmid:27429447","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/27429447","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE/ACM transactions on computational biology and bioinformatics","raw_type":null},{"id":"pmh:oai:europepmc.org:4846266","is_oa":false,"landing_page_url":"http://europepmc.org/pmc/articles/PMC5486920","pdf_url":null,"source":{"id":"https://openalex.org/S4306400806","display_name":"Europe PMC (PubMed Central)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1303153112","host_organization_name":"European Bioinformatics Institute","host_organization_lineage":["https://openalex.org/I1303153112"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:5486920","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/5486920","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE/ACM Trans Comput Biol Bioinform","raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:pubmedcentral.nih.gov:5486920","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/5486920","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE/ACM Trans Comput Biol Bioinform","raw_type":"Text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3291935934","display_name":null,"funder_award_id":"R01GM107145","funder_id":"https://openalex.org/F4320337354","funder_display_name":"National Institute of General Medical Sciences"},{"id":"https://openalex.org/G4221401674","display_name":null,"funder_award_id":"R01 GM107145","funder_id":"https://openalex.org/F4320337354","funder_display_name":"National Institute of General Medical Sciences"}],"funders":[{"id":"https://openalex.org/F4320337354","display_name":"National Institute of General Medical Sciences","ror":"https://ror.org/04q48ey07"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":57,"referenced_works":["https://openalex.org/W74906953","https://openalex.org/W259909490","https://openalex.org/W1500664693","https://openalex.org/W1517198794","https://openalex.org/W1800549457","https://openalex.org/W1844110723","https://openalex.org/W1958889900","https://openalex.org/W1967931674","https://openalex.org/W1983798833","https://openalex.org/W1989037929","https://openalex.org/W2004910511","https://openalex.org/W2010569611","https://openalex.org/W2012370199","https://openalex.org/W2012451988","https://openalex.org/W2012648967","https://openalex.org/W2013170360","https://openalex.org/W2016449808","https://openalex.org/W2021546954","https://openalex.org/W2029674613","https://openalex.org/W2047643451","https://openalex.org/W2055433197","https://openalex.org/W2058151187","https://openalex.org/W2069720347","https://openalex.org/W2074420638","https://openalex.org/W2079748062","https://openalex.org/W2081028405","https://openalex.org/W2082285428","https://openalex.org/W2086173776","https://openalex.org/W2105510466","https://openalex.org/W2107195500","https://openalex.org/W2120448874","https://openalex.org/W2121382432","https://openalex.org/W2131904035","https://openalex.org/W2132996843","https://openalex.org/W2142047467","https://openalex.org/W2155712369","https://openalex.org/W2158396349","https://openalex.org/W2161484642","https://openalex.org/W2163649042","https://openalex.org/W2171231355","https://openalex.org/W2171826252","https://openalex.org/W2173145736","https://openalex.org/W2205975271","https://openalex.org/W2240212332","https://openalex.org/W2329271502","https://openalex.org/W2345930594","https://openalex.org/W2395484564","https://openalex.org/W2998216295","https://openalex.org/W3104422614","https://openalex.org/W4229652772","https://openalex.org/W4242702158","https://openalex.org/W4285719527","https://openalex.org/W6602986003","https://openalex.org/W6638313541","https://openalex.org/W6653341902","https://openalex.org/W6682821030","https://openalex.org/W7066667914"],"related_works":["https://openalex.org/W2978999882","https://openalex.org/W2045155990","https://openalex.org/W4313163053","https://openalex.org/W3141031773","https://openalex.org/W4300973204","https://openalex.org/W3045811229","https://openalex.org/W1595686156","https://openalex.org/W2181392282","https://openalex.org/W4386564352","https://openalex.org/W2952668426"],"abstract_inverted_index":{"Accurate":[0],"prognosis":[1],"of":[2,18,51,87,132,143,154,171,181,192],"outcome":[3,88],"events,":[4],"such":[5],"as":[6,137],"clinical":[7,20,108,124],"procedures":[8],"or":[9],"disease":[10],"diagnosis,":[11],"is":[12,59],"central":[13],"in":[14,74,106],"medicine.":[15],"The":[16],"emergence":[17],"longitudinal":[19],"data,":[21],"like":[22],"the":[23,49,85,103,107,130,141,152,161,179,185,190],"Electronic":[24],"Health":[25],"Records":[26],"(EHR),":[27],"represents":[28],"an":[29],"opportunity":[30],"to":[31,118,128,169],"develop":[32],"automated":[33],"methods":[34],"for":[35,84,122],"predicting":[36],"patient":[37],"outcomes.":[38],"However,":[39],"these":[40,92,116],"data":[41],"are":[42,111,135],"highly":[43],"dimensional":[44],"and":[45,66,114,165],"very":[46],"sparse,":[47],"complicating":[48],"application":[50],"predictive":[52,99,120],"modeling":[53],"techniques.":[54],"Further,":[55],"their":[56],"temporal":[57,67,104,182],"nature":[58],"not":[60],"fully":[61],"exploited":[62],"by":[63],"current":[64],"methods,":[65,187],"abstraction":[68],"was":[69],"recently":[70],"used":[71,136],"which":[72],"results":[73,168],"symbolic":[75,93],"time":[76,94],"intervals":[77],"representation.":[78],"We":[79,150],"present":[80],"Maitreya,":[81,97],"a":[82],"framework":[83],"prediction":[86],"events":[89],"that":[90,110,134,170,178],"leverages":[91],"intervals.":[95],"Using":[96],"learn":[98],"models":[100,121],"based":[101],"on":[102],"patterns":[105,133,183],"records":[109],"prognostic":[112],"markers":[113,117],"use":[115,142,180],"train":[119],"eight":[123],"procedures.":[125],"In":[126,174],"order":[127],"decrease":[129],"number":[131,191],"features,":[138],"we":[139,176],"propose":[140],"three":[144],"one":[145],"class":[146],"feature":[147,163],"selection":[148],"methods.":[149],"evaluate":[151],"performance":[153],"Maitreya":[155],"under":[156],"several":[157],"parameter":[158],"settings,":[159],"including":[160],"one-class":[162],"selection,":[164],"compare":[166],"our":[167],"atemporal":[172,186],"approaches.":[173],"general,":[175],"found":[177],"outperformed":[184],"when":[188],"representing":[189],"pattern":[193],"occurrences.":[194]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":5},{"year":2016,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}