{"id":"https://openalex.org/W3013099093","doi":"https://doi.org/10.1111/coin.12313","title":"Opening the black box: Personalizing type 2 diabetes patients based on their latent phenotype and temporal associated complication rules","display_name":"Opening the black box: Personalizing type 2 diabetes patients based on their latent phenotype and temporal associated complication rules","publication_year":2020,"publication_date":"2020-03-29","ids":{"openalex":"https://openalex.org/W3013099093","doi":"https://doi.org/10.1111/coin.12313","mag":"3013099093"},"language":"en","primary_location":{"id":"doi:10.1111/coin.12313","is_oa":true,"landing_page_url":"https://doi.org/10.1111/coin.12313","pdf_url":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/coin.12313","source":{"id":"https://openalex.org/S56561474","display_name":"Computational Intelligence","issn_l":"0824-7935","issn":["0824-7935","1467-8640"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/coin.12313","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103128438","display_name":"Leila Yousefi","orcid":"https://orcid.org/0000-0003-1952-0674"},"institutions":[{"id":"https://openalex.org/I59433898","display_name":"Brunel University of London","ror":"https://ror.org/00dn4t376","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I59433898"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Leila Yousefi","raw_affiliation_strings":["Department of Computer Science Brunel University London  London UK","Department of Computer Science, Brunel University London, London, UK"],"raw_orcid":"https://orcid.org/0000-0003-1952-0674","affiliations":[{"raw_affiliation_string":"Department of Computer Science Brunel University London  London UK","institution_ids":["https://openalex.org/I59433898"]},{"raw_affiliation_string":"Department of Computer Science, Brunel University London, London, UK","institution_ids":["https://openalex.org/I59433898"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042037650","display_name":"Stephen Swift","orcid":"https://orcid.org/0000-0001-8918-3365"},"institutions":[{"id":"https://openalex.org/I59433898","display_name":"Brunel University of London","ror":"https://ror.org/00dn4t376","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I59433898"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Stephen Swift","raw_affiliation_strings":["Department of Computer Science Brunel University London  London UK","Department of Computer Science, Brunel University London, London, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science Brunel University London  London UK","institution_ids":["https://openalex.org/I59433898"]},{"raw_affiliation_string":"Department of Computer Science, Brunel University London, London, UK","institution_ids":["https://openalex.org/I59433898"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077607362","display_name":"Mahir Arzoky","orcid":null},"institutions":[{"id":"https://openalex.org/I59433898","display_name":"Brunel University of London","ror":"https://ror.org/00dn4t376","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I59433898"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Mahir Arzoky","raw_affiliation_strings":["Department of Computer Science Brunel University London  London UK","Department of Computer Science, Brunel University London, London, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science Brunel University London  London UK","institution_ids":["https://openalex.org/I59433898"]},{"raw_affiliation_string":"Department of Computer Science, Brunel University London, London, UK","institution_ids":["https://openalex.org/I59433898"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019641328","display_name":"Lucia Saachi","orcid":null},"institutions":[{"id":"https://openalex.org/I25217355","display_name":"University of Pavia","ror":"https://ror.org/00s6t1f81","country_code":"IT","type":"education","lineage":["https://openalex.org/I25217355"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Lucia Saachi","raw_affiliation_strings":["Department of Computer Science University of Pavia  Pavia Italy","Department of Computer Science, University of Pavia, Pavia, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science University of Pavia  Pavia Italy","institution_ids":["https://openalex.org/I25217355"]},{"raw_affiliation_string":"Department of Computer Science, University of Pavia, Pavia, Italy","institution_ids":["https://openalex.org/I25217355"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071641712","display_name":"Luca Chiovato","orcid":"https://orcid.org/0000-0001-7457-7353"},"institutions":[{"id":"https://openalex.org/I25217355","display_name":"University of Pavia","ror":"https://ror.org/00s6t1f81","country_code":"IT","type":"education","lineage":["https://openalex.org/I25217355"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Luca Chiovato","raw_affiliation_strings":["Unit of Endocrinology University of Pavia  Pavia Italy","Unit of Endocrinology, University of Pavia, Pavia, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Unit of Endocrinology University of Pavia  Pavia Italy","institution_ids":["https://openalex.org/I25217355"]},{"raw_affiliation_string":"Unit of Endocrinology, University of Pavia, Pavia, Italy","institution_ids":["https://openalex.org/I25217355"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004397914","display_name":"Allan Tucker","orcid":"https://orcid.org/0000-0001-5105-3506"},"institutions":[{"id":"https://openalex.org/I59433898","display_name":"Brunel University of London","ror":"https://ror.org/00dn4t376","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I59433898"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Allan Tucker","raw_affiliation_strings":["Department of Computer Science Brunel University London  London UK","Department of Computer Science, Brunel University London, London, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science Brunel University London  London UK","institution_ids":["https://openalex.org/I59433898"]},{"raw_affiliation_string":"Department of Computer Science, Brunel University London, London, UK","institution_ids":["https://openalex.org/I59433898"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5103128438"],"corresponding_institution_ids":["https://openalex.org/I59433898"],"apc_list":{"value":3450,"currency":"USD","value_usd":3450},"apc_paid":{"value":3450,"currency":"USD","value_usd":3450},"fwci":1.9048,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.89065841,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"37","issue":"4","first_page":"1460","last_page":"1498"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9965999722480774,"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":0.9965999722480774,"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/T10261","display_name":"Genetic Associations and Epidemiology","score":0.9768000245094299,"subfield":{"id":"https://openalex.org/subfields/1311","display_name":"Genetics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10027","display_name":"Diabetes, Cardiovascular Risks, and Lipoproteins","score":0.9753000140190125,"subfield":{"id":"https://openalex.org/subfields/2712","display_name":"Endocrinology, Diabetes and Metabolism"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/disease","display_name":"Disease","score":0.57940274477005},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.5293420553207397},{"id":"https://openalex.org/keywords/black-box","display_name":"Black box","score":0.5094085335731506},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.45211541652679443},{"id":"https://openalex.org/keywords/clinical-phenotype","display_name":"Clinical phenotype","score":0.44782698154449463},{"id":"https://openalex.org/keywords/type-2-diabetes","display_name":"Type 2 diabetes","score":0.42861172556877136},{"id":"https://openalex.org/keywords/phenotype","display_name":"Phenotype","score":0.42589879035949707},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.42165786027908325},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.41429752111434937},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3889595568180084},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3441486954689026},{"id":"https://openalex.org/keywords/diabetes-mellitus","display_name":"Diabetes mellitus","score":0.3193396329879761},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.15064534544944763},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.10542187094688416}],"concepts":[{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.57940274477005},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.5293420553207397},{"id":"https://openalex.org/C94966114","wikidata":"https://www.wikidata.org/wiki/Q29256","display_name":"Black box","level":2,"score":0.5094085335731506},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.45211541652679443},{"id":"https://openalex.org/C3020646490","wikidata":"https://www.wikidata.org/wiki/Q25203551","display_name":"Clinical phenotype","level":4,"score":0.44782698154449463},{"id":"https://openalex.org/C2777180221","wikidata":"https://www.wikidata.org/wiki/Q3025883","display_name":"Type 2 diabetes","level":3,"score":0.42861172556877136},{"id":"https://openalex.org/C127716648","wikidata":"https://www.wikidata.org/wiki/Q104053","display_name":"Phenotype","level":3,"score":0.42589879035949707},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.42165786027908325},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.41429752111434937},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3889595568180084},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3441486954689026},{"id":"https://openalex.org/C555293320","wikidata":"https://www.wikidata.org/wiki/Q12206","display_name":"Diabetes mellitus","level":2,"score":0.3193396329879761},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.15064534544944763},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.10542187094688416},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C134018914","wikidata":"https://www.wikidata.org/wiki/Q162606","display_name":"Endocrinology","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C99454951","wikidata":"https://www.wikidata.org/wiki/Q932068","display_name":"Environmental health","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1111/coin.12313","is_oa":true,"landing_page_url":"https://doi.org/10.1111/coin.12313","pdf_url":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/coin.12313","source":{"id":"https://openalex.org/S56561474","display_name":"Computational Intelligence","issn_l":"0824-7935","issn":["0824-7935","1467-8640"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:bura.brunel.ac.uk:2438/20607","is_oa":true,"landing_page_url":"https://bura.brunel.ac.uk/handle/2438/20607","pdf_url":null,"source":{"id":"https://openalex.org/S4306401473","display_name":"Brunel University Research Archive (BURA) (Brunel University London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I59433898","host_organization_name":"Brunel University of London","host_organization_lineage":["https://openalex.org/I59433898"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Article"},{"id":"pmh:oai:v-lib-bura1.brunel.ac.uk:2438/20607","is_oa":false,"landing_page_url":"http://doi.org/10.1111/coin.12313","pdf_url":null,"source":{"id":"https://openalex.org/S4306401473","display_name":"Brunel University Research Archive (BURA) (Brunel University London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I59433898","host_organization_name":"Brunel University of London","host_organization_lineage":["https://openalex.org/I59433898"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Article"}],"best_oa_location":{"id":"doi:10.1111/coin.12313","is_oa":true,"landing_page_url":"https://doi.org/10.1111/coin.12313","pdf_url":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/coin.12313","source":{"id":"https://openalex.org/S56561474","display_name":"Computational Intelligence","issn_l":"0824-7935","issn":["0824-7935","1467-8640"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.7900000214576721,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W3013099093.pdf"},"referenced_works_count":47,"referenced_works":["https://openalex.org/W33456978","https://openalex.org/W55101911","https://openalex.org/W78245881","https://openalex.org/W92540498","https://openalex.org/W1164941284","https://openalex.org/W1768619703","https://openalex.org/W1844110723","https://openalex.org/W1967430507","https://openalex.org/W1967721236","https://openalex.org/W1981852586","https://openalex.org/W1985690171","https://openalex.org/W2042572647","https://openalex.org/W2046339948","https://openalex.org/W2053365438","https://openalex.org/W2059887610","https://openalex.org/W2067842758","https://openalex.org/W2076450470","https://openalex.org/W2086173776","https://openalex.org/W2096429513","https://openalex.org/W2117168324","https://openalex.org/W2122182414","https://openalex.org/W2122540544","https://openalex.org/W2124788738","https://openalex.org/W2126946832","https://openalex.org/W2144267426","https://openalex.org/W2147165687","https://openalex.org/W2150706940","https://openalex.org/W2151363206","https://openalex.org/W2155326729","https://openalex.org/W2163850436","https://openalex.org/W2166205682","https://openalex.org/W2166559705","https://openalex.org/W2285495449","https://openalex.org/W2326339805","https://openalex.org/W2394309960","https://openalex.org/W2752336761","https://openalex.org/W2768426515","https://openalex.org/W2883252565","https://openalex.org/W2913033917","https://openalex.org/W2914828897","https://openalex.org/W2959587146","https://openalex.org/W2961234535","https://openalex.org/W2964304683","https://openalex.org/W2964650631","https://openalex.org/W2965970765","https://openalex.org/W2998574808","https://openalex.org/W6627551785"],"related_works":["https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2973263109","https://openalex.org/W2314682585","https://openalex.org/W3020075806","https://openalex.org/W4299494032","https://openalex.org/W2067376269","https://openalex.org/W2419471986","https://openalex.org/W3046549861","https://openalex.org/W4244333378"],"abstract_inverted_index":{"Abstract":[0],"It":[1],"is":[2,22],"widely":[3],"considered":[4],"that":[5],"approximately":[6],"10%":[7],"of":[8,19,51,96,111,125,147],"the":[9,17,33,37,49,56,94,97,137,143,162,169,175],"population":[10],"suffers":[11],"from":[12,67],"type":[13],"2":[14],"diabetes.":[15],"Unfortunately,":[16],"impact":[18],"this":[20,73,77,105],"disease":[21,34,38],"underestimated.":[23],"Patient's":[24],"mortality":[25],"often":[26,47],"occurs":[27],"due":[28],"to":[29,64,92,121,160],"complications":[30,152],"caused":[31],"by":[32,107],"and":[35,59,69,79,116,165],"not":[36],"itself.":[39],"Many":[40],"techniques":[41],"utilized":[42],"in":[43,48,119,141,168,174],"modeling":[44],"diseases":[45],"are":[46,61],"form":[50],"a":[52,86,109],"\u201cblack":[53],"box\u201d":[54],"where":[55],"internal":[57],"workings":[58],"complexities":[60,95],"extremely":[62],"difficult":[63],"understand,":[65],"both":[66],"practitioners'":[68],"patients'":[70,176],"perspective.":[71],"In":[72],"work,":[74],"we":[75],"address":[76],"issue":[78],"present":[80],"an":[81,90],"informative":[82],"model/pattern,":[83],"known":[84],"as":[85],"\u201clatent":[87],"phenotype,\u201d":[88],"with":[89,127],"aim":[91],"capture":[93],"associated":[98],"complications'":[99],"over":[100],"time.":[101],"We":[102,154],"further":[103],"extend":[104],"idea":[106],"using":[108,172],"combination":[110],"temporal":[112],"association":[113],"rule":[114],"mining":[115],"unsupervised":[117],"learning":[118],"order":[120],"find":[122],"explainable":[123],"subgroups":[124,146],"patients":[126,148],"more":[128],"personalized":[129],"prediction.":[130],"Our":[131],"extensive":[132],"findings":[133],"show":[134],"how":[135,158],"uncovering":[136],"latent":[138],"phenotype":[139],"aids":[140],"distinguishing":[142],"disparities":[144],"among":[145],"based":[149],"on":[150],"their":[151],"patterns.":[153],"gain":[155],"insight":[156],"into":[157],"best":[159],"enhance":[161],"prediction":[163],"performance":[164],"reduce":[166],"bias":[167],"models":[170],"applied":[171],"uncertainty":[173],"data.":[177]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2}],"updated_date":"2026-05-22T06:13:13.366637","created_date":"2025-10-10T00:00:00"}