{"id":"https://openalex.org/W4393583591","doi":"https://doi.org/10.3233/ida-230314","title":"Identifying longevity profiles from longitudinal data through factor analysis and biclustering","display_name":"Identifying longevity profiles from longitudinal data through factor analysis and biclustering","publication_year":2024,"publication_date":"2024-04-02","ids":{"openalex":"https://openalex.org/W4393583591","doi":"https://doi.org/10.3233/ida-230314"},"language":"en","primary_location":{"id":"doi:10.3233/ida-230314","is_oa":false,"landing_page_url":"https://doi.org/10.3233/ida-230314","pdf_url":null,"source":{"id":"https://openalex.org/S2498839158","display_name":"Intelligent Data Analysis","issn_l":"1088-467X","issn":["1088-467X","1571-4128"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Data Analysis","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/A5042985365","display_name":"Marta D.M. Noronha","orcid":"https://orcid.org/0000-0002-2992-8422"},"institutions":[{"id":"https://openalex.org/I170935008","display_name":"Pontif\u00edcia Universidade Cat\u00f3lica de Minas Gerais","ror":"https://ror.org/03j1rr444","country_code":"BR","type":"education","lineage":["https://openalex.org/I170935008"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"Marta D.M. Noronha","raw_affiliation_strings":["Department of Computer Science, Pontifical Catholic University of Minas Gerais, Minas Gerais, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Pontifical Catholic University of Minas Gerais, Minas Gerais, Brazil","institution_ids":["https://openalex.org/I170935008"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056686523","display_name":"Luis E. Z\u00e1rate","orcid":"https://orcid.org/0000-0001-7063-1658"},"institutions":[{"id":"https://openalex.org/I170935008","display_name":"Pontif\u00edcia Universidade Cat\u00f3lica de Minas Gerais","ror":"https://ror.org/03j1rr444","country_code":"BR","type":"education","lineage":["https://openalex.org/I170935008"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Luis E. Z\u00e1rate","raw_affiliation_strings":["Department of Computer Science, Pontifical Catholic University of Minas Gerais, Minas Gerais, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Pontifical Catholic University of Minas Gerais, Minas Gerais, Brazil","institution_ids":["https://openalex.org/I170935008"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5042985365"],"corresponding_institution_ids":["https://openalex.org/I170935008"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.06187793,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"28","issue":"6","first_page":"1555","last_page":"1578"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10866","display_name":"Nutritional Studies and Diet","score":0.9521999955177307,"subfield":{"id":"https://openalex.org/subfields/2739","display_name":"Public Health, Environmental and Occupational Health"},"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/T10866","display_name":"Nutritional Studies and Diet","score":0.9521999955177307,"subfield":{"id":"https://openalex.org/subfields/2739","display_name":"Public Health, Environmental and Occupational Health"},"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/T12011","display_name":"Insurance, Mortality, Demography, Risk Management","score":0.9107999801635742,"subfield":{"id":"https://openalex.org/subfields/3317","display_name":"Demography"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/longevity","display_name":"Longevity","score":0.8031365871429443},{"id":"https://openalex.org/keywords/biclustering","display_name":"Biclustering","score":0.6342648267745972},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6164069175720215},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.5143581628799438},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.47279685735702515},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4489183723926544},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.44745582342147827},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.4387485682964325},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42122119665145874},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39221861958503723},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.3587911128997803},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10431930422782898},{"id":"https://openalex.org/keywords/gerontology","display_name":"Gerontology","score":0.06351417303085327}],"concepts":[{"id":"https://openalex.org/C2776759703","wikidata":"https://www.wikidata.org/wiki/Q1066907","display_name":"Longevity","level":2,"score":0.8031365871429443},{"id":"https://openalex.org/C144817290","wikidata":"https://www.wikidata.org/wiki/Q2976575","display_name":"Biclustering","level":5,"score":0.6342648267745972},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6164069175720215},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.5143581628799438},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.47279685735702515},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4489183723926544},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.44745582342147827},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.4387485682964325},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42122119665145874},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39221861958503723},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.3587911128997803},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10431930422782898},{"id":"https://openalex.org/C74909509","wikidata":"https://www.wikidata.org/wiki/Q10387","display_name":"Gerontology","level":1,"score":0.06351417303085327},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/ida-230314","is_oa":false,"landing_page_url":"https://doi.org/10.3233/ida-230314","pdf_url":null,"source":{"id":"https://openalex.org/S2498839158","display_name":"Intelligent Data Analysis","issn_l":"1088-467X","issn":["1088-467X","1571-4128"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Data Analysis","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7200000286102295}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1556007540","https://openalex.org/W1590171802","https://openalex.org/W1985710750","https://openalex.org/W2006691174","https://openalex.org/W2036997338","https://openalex.org/W2077223919","https://openalex.org/W2080278541","https://openalex.org/W2088477804","https://openalex.org/W2105883975","https://openalex.org/W2109550515","https://openalex.org/W2116231131","https://openalex.org/W2133097426","https://openalex.org/W2144544802","https://openalex.org/W2157302779","https://openalex.org/W2179299242","https://openalex.org/W2303661888","https://openalex.org/W2319523112","https://openalex.org/W2326733522","https://openalex.org/W2405658205","https://openalex.org/W2522330780","https://openalex.org/W2547058198","https://openalex.org/W2594197256","https://openalex.org/W2789892275","https://openalex.org/W2891774386","https://openalex.org/W2904441284","https://openalex.org/W3014178346","https://openalex.org/W3132537781","https://openalex.org/W3148748093","https://openalex.org/W4213216347","https://openalex.org/W4214930042","https://openalex.org/W4286253367","https://openalex.org/W6813678250","https://openalex.org/W6911259190"],"related_works":["https://openalex.org/W1995622179","https://openalex.org/W1484111231","https://openalex.org/W4391160746","https://openalex.org/W1552543208","https://openalex.org/W2074396517","https://openalex.org/W2166963679","https://openalex.org/W2187269125","https://openalex.org/W1641615907","https://openalex.org/W3089231081","https://openalex.org/W2093956241"],"abstract_inverted_index":{"Characterizing":[0],"longevity":[1,55,118,145,171],"profiles":[2,56,172],"from":[3,45,106,173],"longitudinal":[4,14,175],"studies":[5,176],"is":[6,146,180],"a":[7,29,62,94,101],"task":[8,32],"with":[9],"many":[10],"challenges.":[11],"Firstly,":[12],"the":[13,21,46,98,107,134,140,149,152,156,159],"databases":[15],"usually":[16],"have":[17],"high":[18],"dimensionality,":[19],"and":[20,25,76,97,155],"similarities":[22],"between":[23,151],"long-lived":[24,129],"non-long-lived":[26],"records":[27],"are":[28,104],"highly":[30],"burdening":[31],"for":[33,64,67,183],"profile":[34,184],"characterization.":[35],"Addressing":[36],"these":[37],"issues,":[38],"in":[39],"this":[40,164],"work,":[41],"we":[42],"use":[43],"data":[44,58,69],"English":[47],"Longitudinal":[48],"Study":[49],"of":[50,158],"Ageing":[51],"(ELSA-UK)":[52],"to":[53,81,126,133,148,169],"characterize":[54],"through":[57,71],"mining.":[59],"We":[60,78,120,161],"propose":[61],"method":[63],"feature":[65],"engineering":[66],"reducing":[68],"dimensionality":[70],"merging":[72],"techniques,":[73],"factor":[74,142,179],"analysis":[75],"biclustering.":[77],"apply":[79],"biclustering":[80],"select":[82],"relevant":[83,182],"features":[84,124],"discriminating":[85],"both":[86,138],"profiles.":[87,119],"Two":[88],"classification":[89],"models,":[90,139],"one":[91],"based":[92],"on":[93,100],"decision":[95],"tree":[96],"other":[99,174],"random":[102],"forest,":[103],"built":[105],"preprocessed":[108],"dataset.":[109],"Experiments":[110],"show":[111],"that":[112,143,163,178],"our":[113],"methodology":[114,165],"can":[115,166],"successfully":[116],"discriminate":[117],"identify":[121,170],"insights":[122],"into":[123],"contributing":[125],"individuals":[127],"being":[128],"or":[130],"non-long-lived.":[131],"According":[132],"results":[135],"presented":[136],"by":[137],"main":[141],"impacts":[144],"related":[147],"correlations":[150],"economic":[153],"situation":[154],"mobility":[157],"elderly.":[160],"suggest":[162],"be":[167],"applied":[168],"since":[177],"deemed":[181],"classification.":[185]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
