{"id":"https://openalex.org/W4415003943","doi":"https://doi.org/10.1109/acit65614.2025.11185617","title":"Diagnosis Heart Attack and Stroke Risk using Machine Learning Algorithms: Risk Classification and Explanation of Diagnostic Reasons with LIME","display_name":"Diagnosis Heart Attack and Stroke Risk using Machine Learning Algorithms: Risk Classification and Explanation of Diagnostic Reasons with LIME","publication_year":2025,"publication_date":"2025-09-17","ids":{"openalex":"https://openalex.org/W4415003943","doi":"https://doi.org/10.1109/acit65614.2025.11185617"},"language":"en","primary_location":{"id":"doi:10.1109/acit65614.2025.11185617","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acit65614.2025.11185617","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 15th International Conference on Advanced Computer Information Technologies (ACIT)","raw_type":"proceedings-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/A5119925149","display_name":"Kaz\u0131m Tibet Sar","orcid":null},"institutions":[{"id":"https://openalex.org/I2799978770","display_name":"X-Fab (Germany)","ror":"https://ror.org/030bh9196","country_code":"DE","type":"company","lineage":["https://openalex.org/I2799978770"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Kaz\u0131m Tibet Sar","raw_affiliation_strings":["Fırat University,Department of Technology and Information Management,Elazığ,Türkiye"],"affiliations":[{"raw_affiliation_string":"Fırat University,Department of Technology and Information Management,Elazığ,Türkiye","institution_ids":["https://openalex.org/I2799978770"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028134655","display_name":"Buket Kaya","orcid":"https://orcid.org/0000-0001-9505-181X"},"institutions":[{"id":"https://openalex.org/I2799978770","display_name":"X-Fab (Germany)","ror":"https://ror.org/030bh9196","country_code":"DE","type":"company","lineage":["https://openalex.org/I2799978770"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Buket Kaya","raw_affiliation_strings":["Fırat University,Department of Electronics and Automation,Elazığ,Türkiye"],"affiliations":[{"raw_affiliation_string":"Fırat University,Department of Electronics and Automation,Elazığ,Türkiye","institution_ids":["https://openalex.org/I2799978770"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5119925149"],"corresponding_institution_ids":["https://openalex.org/I2799978770"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.32809406,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"824","last_page":"827"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.49900001287460327,"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"}},"topics":[{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.49900001287460327,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5954999923706055},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5716000199317932},{"id":"https://openalex.org/keywords/stroke","display_name":"Stroke (engine)","score":0.5012000203132629},{"id":"https://openalex.org/keywords/lime","display_name":"Lime","score":0.3084999918937683},{"id":"https://openalex.org/keywords/heart-rate","display_name":"Heart rate","score":0.30329999327659607},{"id":"https://openalex.org/keywords/medical-equipment","display_name":"Medical equipment","score":0.296099990606308},{"id":"https://openalex.org/keywords/blood-pressure","display_name":"Blood pressure","score":0.2883000075817108}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6225000023841858},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6205000281333923},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5954999923706055},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5716000199317932},{"id":"https://openalex.org/C2780645631","wikidata":"https://www.wikidata.org/wiki/Q671554","display_name":"Stroke (engine)","level":2,"score":0.5012000203132629},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.475600004196167},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3149000108242035},{"id":"https://openalex.org/C2778218555","wikidata":"https://www.wikidata.org/wiki/Q250423","display_name":"Lime","level":2,"score":0.3084999918937683},{"id":"https://openalex.org/C2777953023","wikidata":"https://www.wikidata.org/wiki/Q1073121","display_name":"Heart rate","level":3,"score":0.30329999327659607},{"id":"https://openalex.org/C513323569","wikidata":"https://www.wikidata.org/wiki/Q6554101","display_name":"Medical equipment","level":2,"score":0.296099990606308},{"id":"https://openalex.org/C84393581","wikidata":"https://www.wikidata.org/wiki/Q82642","display_name":"Blood pressure","level":2,"score":0.2883000075817108},{"id":"https://openalex.org/C2777267654","wikidata":"https://www.wikidata.org/wiki/Q3519023","display_name":"Test (biology)","level":2,"score":0.28060001134872437},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.2793999910354614},{"id":"https://openalex.org/C534262118","wikidata":"https://www.wikidata.org/wiki/Q177719","display_name":"Medical diagnosis","level":2,"score":0.2718000113964081},{"id":"https://openalex.org/C545542383","wikidata":"https://www.wikidata.org/wiki/Q2751242","display_name":"Medical emergency","level":1,"score":0.27059999108314514},{"id":"https://openalex.org/C12174686","wikidata":"https://www.wikidata.org/wiki/Q1058438","display_name":"Risk assessment","level":2,"score":0.267300009727478},{"id":"https://openalex.org/C1862650","wikidata":"https://www.wikidata.org/wiki/Q186005","display_name":"Physical therapy","level":1,"score":0.26339998841285706},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.26089999079704285},{"id":"https://openalex.org/C2778198053","wikidata":"https://www.wikidata.org/wiki/Q181754","display_name":"Heart failure","level":2,"score":0.2590999901294708},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.2540000081062317}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/acit65614.2025.11185617","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acit65614.2025.11185617","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 15th International Conference on Advanced Computer Information Technologies (ACIT)","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":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"A":[0],"heart":[1,22,37,84],"attack":[2],"is":[3,43],"a":[4,44],"condition":[5,46],"that":[6,16,47],"can":[7,54],"occur":[8],"due":[9,57],"to":[10,23,35,58,61,111,131,194],"the":[11,21,27,36,59,107,122,133,136,139,142,145,174,182,189,198,202],"blockage":[12],"of":[13,26,40,68,141],"blood":[14,18,63],"vessels":[15],"carry":[17],"pumped":[19],"by":[20,74,201],"other":[24],"parts":[25],"body,":[28],"hereditary":[29],"factors,":[30],"or":[31,118],"organ":[32],"failure":[33],"leading":[34],"being":[38],"deprived":[39],"oxygen.":[41],"It":[42],"life-threatening":[45],"may":[48],"result":[49],"in":[50,70,97,170],"death.":[51],"Stroke":[52],"problems":[53],"also":[55],"arise":[56],"inability":[60],"pump":[62],"properly.":[64],"In":[65],"2023,":[66],"33.4%":[67],"deaths":[69],"Turkey":[71],"were":[72,100,109,168],"caused":[73],"cardiovascular":[75],"diseases.":[76],"This":[77],"study":[78,99],"includes":[79],"health":[80],"findings,":[81],"factors":[82],"affecting":[83],"health,":[85],"and":[86,92,106,138,164],"test":[87],"results":[88,108],"from":[89],"588":[90],"women":[91],"1300":[93],"men.":[94],"The":[95],"analyses":[96],"this":[98,171],"conducted":[101],"using":[102],"machine":[103,175],"learning":[104,148,176],"algorithms,":[105],"used":[110],"make":[112],"predictions":[113,137],"categorized":[114],"as":[115,152],"high":[116],"risk":[117],"low":[119],"risk.":[120],"Furthermore,":[121],"LIME":[123,190],"(Local":[124],"Interpretable":[125],"Model-Agnostic":[126],"Explanations)":[127],"method":[128,191],"was":[129,192],"applied":[130],"explain":[132],"reasons":[134],"for":[135],"weights":[140],"features":[143],"influencing":[144],"predictions.":[146],"Machine":[147],"(ML)":[149],"methods":[150],"such":[151],"Random":[153,179],"Forest,":[154],"XGBoost,":[155],"Decision":[156],"Tree,":[157],"Naive":[158],"Bayes,":[159],"Gradient":[160],"Boosting,":[161],"K-Nearest":[162],"Neighbors,":[163],"Support":[165],"Vector":[166],"Machines":[167],"utilized":[169],"study.":[172],"Among":[173],"algorithms":[177],"used,":[178],"Forest":[180],"achieved":[181],"highest":[183],"success":[184],"rate":[185],"with":[186],"96.82%.":[187],"Additionally,":[188],"employed":[193],"provide":[195],"examples":[196],"explaining":[197],"decisions":[199],"made":[200],"algorithms.":[203]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-10T00:00:00"}