{"id":"https://openalex.org/W4387092392","doi":"https://doi.org/10.1109/access.2023.3320057","title":"EXplainable AI for Decision Support to Obesity Comorbidities Diagnosis","display_name":"EXplainable AI for Decision Support to Obesity Comorbidities Diagnosis","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4387092392","doi":"https://doi.org/10.1109/access.2023.3320057"},"language":"en","primary_location":{"id":"doi:10.1109/access.2023.3320057","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3320057","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10265033.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10265033.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5016088075","display_name":"Grazia Veronica Aiosa","orcid":"https://orcid.org/0000-0003-4974-6172"},"institutions":[{"id":"https://openalex.org/I39063666","display_name":"University of Catania","ror":"https://ror.org/03a64bh57","country_code":"IT","type":"education","lineage":["https://openalex.org/I39063666"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Grazia V. Aiosa","raw_affiliation_strings":["Dipartimento di Ingegneria Elettrica, Elettronica ed Informatica, Università degli Studi di Catania, Catania, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dipartimento di Ingegneria Elettrica, Elettronica ed Informatica, Università degli Studi di Catania, Catania, Italy","institution_ids":["https://openalex.org/I39063666"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010989172","display_name":"Maurizio Palesi","orcid":"https://orcid.org/0000-0003-3129-0664"},"institutions":[{"id":"https://openalex.org/I112862951","display_name":"University of Messina","ror":"https://ror.org/05ctdxz19","country_code":"IT","type":"education","lineage":["https://openalex.org/I112862951"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Maurizio Palesi","raw_affiliation_strings":["Dipartimento di Ingegneria, Università degli Studi di Messina, Messina, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dipartimento di Ingegneria, Università degli Studi di Messina, Messina, Italy","institution_ids":["https://openalex.org/I112862951"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070932451","display_name":"Francesca Sapuppo","orcid":"https://orcid.org/0000-0001-8772-2759"},"institutions":[{"id":"https://openalex.org/I39063666","display_name":"University of Catania","ror":"https://ror.org/03a64bh57","country_code":"IT","type":"education","lineage":["https://openalex.org/I39063666"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Francesca Sapuppo","raw_affiliation_strings":["Dipartimento di Ingegneria Elettrica, Elettronica ed Informatica, Università degli Studi di Catania, Catania, Italy"],"raw_orcid":"https://orcid.org/0000-0001-8772-2759","affiliations":[{"raw_affiliation_string":"Dipartimento di Ingegneria Elettrica, Elettronica ed Informatica, Università degli Studi di Catania, Catania, Italy","institution_ids":["https://openalex.org/I39063666"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":3.7527,"has_fulltext":true,"cited_by_count":23,"citation_normalized_percentile":{"value":0.94577233,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"11","issue":null,"first_page":"107767","last_page":"107782"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.9955999851226807,"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"}},"topics":[{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.9955999851226807,"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/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.9854999780654907,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9750999808311462,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6230400800704956},{"id":"https://openalex.org/keywords/decision-support-system","display_name":"Decision support system","score":0.5038260817527771},{"id":"https://openalex.org/keywords/obesity","display_name":"Obesity","score":0.41305097937583923},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3463301360607147},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.2867852449417114},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.12116110324859619}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6230400800704956},{"id":"https://openalex.org/C107327155","wikidata":"https://www.wikidata.org/wiki/Q330268","display_name":"Decision support system","level":2,"score":0.5038260817527771},{"id":"https://openalex.org/C511355011","wikidata":"https://www.wikidata.org/wiki/Q12174","display_name":"Obesity","level":2,"score":0.41305097937583923},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3463301360607147},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.2867852449417114},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.12116110324859619}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2023.3320057","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3320057","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10265033.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:91bb75a42f3d4c7a9fdf733c92239a31","is_oa":true,"landing_page_url":"https://doaj.org/article/91bb75a42f3d4c7a9fdf733c92239a31","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 11, Pp 107767-107782 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2023.3320057","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3320057","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10265033.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.4399999976158142,"display_name":"Good health and well-being"}],"awards":[{"id":"https://openalex.org/G2484832597","display_name":null,"funder_award_id":"2014-2020","funder_id":"https://openalex.org/F4320321873","funder_display_name":"Ministero dell\u2019Istruzione, dell\u2019Universit\u00e0 e della Ricerca"},{"id":"https://openalex.org/G5634946813","display_name":null,"funder_award_id":"2014-2020","funder_id":"https://openalex.org/F4320335322","funder_display_name":"European Regional Development Fund"},{"id":"https://openalex.org/G7107310588","display_name":null,"funder_award_id":"P.O. FESR SICILIA 2014-2020 PRE-CUBE ref.08620100","funder_id":"https://openalex.org/F4320321873","funder_display_name":"Ministero dell\u2019Istruzione, dell\u2019Universit\u00e0 e della Ricerca"}],"funders":[{"id":"https://openalex.org/F4320321873","display_name":"Ministero dell\u2019Istruzione, dell\u2019Universit\u00e0 e della Ricerca","ror":"https://ror.org/0166hxq48"},{"id":"https://openalex.org/F4320335322","display_name":"European Regional Development Fund","ror":"https://ror.org/00k4n6c32"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4387092392.pdf","grobid_xml":"https://content.openalex.org/works/W4387092392.grobid-xml"},"referenced_works_count":14,"referenced_works":["https://openalex.org/W1906793157","https://openalex.org/W1994014704","https://openalex.org/W2024718835","https://openalex.org/W2080793954","https://openalex.org/W2970885630","https://openalex.org/W3021083477","https://openalex.org/W3090765916","https://openalex.org/W3121087114","https://openalex.org/W3130750832","https://openalex.org/W3135662868","https://openalex.org/W3147514193","https://openalex.org/W4288770848","https://openalex.org/W4311576974","https://openalex.org/W4317426771"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"This":[0,215],"paper":[1],"describes":[2],"the":[3,14,25,38,58,61,65,142,182,188,192,196,227,230],"implementation":[4],"of":[5,18,27,60,108,199],"a":[6,73,121,162,233],"comprehensive":[7],"clinical":[8,231],"decision":[9],"support":[10],"system":[11],"(CDSS)":[12],"for":[13,24,117,135,145,154,181],"risk":[15,118,158,212],"factors":[16],"prediction":[17,160],"comorbidities":[19,32],"related":[20],"to":[21,64,140,191,209,223,226],"obesity":[22,237],"and":[23,33,45,101,105,120,147,150,161,229,238,248],"characterization":[26],"indirect":[28,200],"connections":[29,207],"between":[30,41],"such":[31],"non-communicable":[34,68,109],"diseases.":[35],"In":[36,173],"particular,":[37],"direct":[39],"correlation":[40],"obesity,":[42],"diabetes,":[43],"cardiovascular,":[44],"heart":[46,148],"disease":[47,110,137,201],"is":[48,70,123,167,179,203],"analyzed":[49,71],"by":[50,205,220],"using":[51],"machine":[52],"learning":[53],"(ML)":[54],"predictive":[55,89],"models,":[56],"while":[57],"connection":[59],"co-occurring":[62],"disorders":[63],"numerous":[66],"additional":[67],"diseases":[69],"via":[72],"graph-based":[74,106,197],"user":[75],"interface.":[76],"The":[77,132],"CDSS":[78],"here":[79],"proposed":[80],"is,":[81],"therefore,":[82],"structured":[83],"with":[84],"three":[85],"main":[86],"components:":[87],"ML":[88,113],"models":[90,114],"based":[91,126],"on":[92,127,169,187,236],"publicly":[93],"available":[94],"datasets,":[95],"explainable":[96],"artificial":[97],"intelligence":[98],"(XAI)":[99],"local":[100,164],"global":[102,176,234],"model":[103,134,165,177],"interpretation,":[104],"representation":[107],"connections.":[111],"Multiple":[112],"are":[115],"presented":[116],"assessment":[119],"comparison":[122],"carried":[124],"out":[125],"performance":[128,130],"key":[129],"indicators.":[131],"best-performing":[133],"each":[136],"was":[138],"proved":[139],"be:":[141],"multi-layer":[143],"perceptron":[144],"diabetes":[146],"disease,":[149],"extreme":[151],"gradient":[152],"boosting":[153],"cardiovascular":[155],"disease.":[156],"Comorbidities":[157],"factor":[159,213],"XAI":[163,175],"explanation":[166],"performed":[168,204],"significant":[170],"case":[171],"studies.":[172],"addition,":[174],"interpretation":[178],"given":[180],"entire":[183],"dataset":[184],"providing":[185],"insights":[186],"features\u2019":[189],"contribution":[190],"models\u2019":[193],"implementation.":[194],"Moreover,":[195],"visualization":[198],"co-occurrence":[202],"filtering":[206],"according":[208,225],"different":[210],"relative":[211],"thresholds.":[214],"interface":[216],"can":[217],"be":[218],"exploited":[219],"healthcare":[221],"professionals":[222],"obtain,":[224],"needs":[228],"approach,":[232],"perspective":[235],"its":[239],"associated":[240],"pathologies":[241],"prevention":[242],"as":[243,245],"well":[244],"long-term":[246],"treatment":[247],"care":[249],"provision.":[250]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}