{"id":"https://openalex.org/W4413051132","doi":"https://doi.org/10.3233/shti250979","title":"Predicting Diabetes Using Convolutional Neural Networks and EKG Entropy Analysis","display_name":"Predicting Diabetes Using Convolutional Neural Networks and EKG Entropy Analysis","publication_year":2025,"publication_date":"2025-08-07","ids":{"openalex":"https://openalex.org/W4413051132","doi":"https://doi.org/10.3233/shti250979","pmid":"https://pubmed.ncbi.nlm.nih.gov/40775997"},"language":"en","primary_location":{"id":"doi:10.3233/shti250979","is_oa":true,"landing_page_url":"https://doi.org/10.3233/shti250979","pdf_url":null,"source":{"id":"https://openalex.org/S4210179765","display_name":"Studies in health technology and informatics","issn_l":"0926-9630","issn":["0926-9630","1879-8365"],"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":"book series"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Studies in Health Technology and Informatics","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.3233/shti250979","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5066799633","display_name":"Sayonara de F\u00e1tima Faria Barbosa","orcid":"https://orcid.org/0000-0002-2342-3300"},"institutions":[{"id":"https://openalex.org/I92156820","display_name":"University of Cincinnati Medical Center","ror":"https://ror.org/02p72h367","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I92156820"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sayonara de F\u00e1tima F. Barbosa","raw_affiliation_strings":["University of Cincinnati College of Nursing, USA"],"raw_orcid":"https://orcid.org/0000-0002-2342-3300","affiliations":[{"raw_affiliation_string":"University of Cincinnati College of Nursing, USA","institution_ids":["https://openalex.org/I92156820"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036634984","display_name":"Fabio Kau\u00ea Araujo Da Silva","orcid":"https://orcid.org/0009-0007-5404-1421"},"institutions":[{"id":"https://openalex.org/I3017928408","display_name":"Universidade do Estado de Mato Grosso","ror":"https://ror.org/02cbymn47","country_code":"BR","type":"education","lineage":["https://openalex.org/I3017928408"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Fabio J. Silva","raw_affiliation_strings":["Mato Grosso State Department of Health, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Mato Grosso State Department of Health, Brazil","institution_ids":["https://openalex.org/I3017928408"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.41930116,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"329","issue":null,"first_page":"946","last_page":"950"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10745","display_name":"Heart Rate Variability and Autonomic Control","score":0.9901999831199646,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"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/T10745","display_name":"Heart Rate Variability and Autonomic Control","score":0.9901999831199646,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"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/T11021","display_name":"ECG Monitoring and Analysis","score":0.9861999750137329,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"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/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.920199990272522,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6995742321014404},{"id":"https://openalex.org/keywords/heart-rate-variability","display_name":"Heart rate variability","score":0.5702885389328003},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5356585383415222},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5283233523368835},{"id":"https://openalex.org/keywords/approximate-entropy","display_name":"Approximate entropy","score":0.513177216053009},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4980473518371582},{"id":"https://openalex.org/keywords/subclinical-infection","display_name":"Subclinical infection","score":0.48334214091300964},{"id":"https://openalex.org/keywords/diabetes-mellitus","display_name":"Diabetes mellitus","score":0.4758598208427429},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.468589723110199},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3276689648628235},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2844030559062958},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.27007246017456055},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.24710899591445923},{"id":"https://openalex.org/keywords/heart-rate","display_name":"Heart rate","score":0.13907623291015625}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6995742321014404},{"id":"https://openalex.org/C71635504","wikidata":"https://www.wikidata.org/wiki/Q933954","display_name":"Heart rate variability","level":4,"score":0.5702885389328003},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5356585383415222},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5283233523368835},{"id":"https://openalex.org/C86859247","wikidata":"https://www.wikidata.org/wiki/Q4781760","display_name":"Approximate entropy","level":3,"score":0.513177216053009},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4980473518371582},{"id":"https://openalex.org/C113280763","wikidata":"https://www.wikidata.org/wiki/Q2326546","display_name":"Subclinical infection","level":2,"score":0.48334214091300964},{"id":"https://openalex.org/C555293320","wikidata":"https://www.wikidata.org/wiki/Q12206","display_name":"Diabetes mellitus","level":2,"score":0.4758598208427429},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.468589723110199},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3276689648628235},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2844030559062958},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.27007246017456055},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.24710899591445923},{"id":"https://openalex.org/C2777953023","wikidata":"https://www.wikidata.org/wiki/Q1073121","display_name":"Heart rate","level":3,"score":0.13907623291015625},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C84393581","wikidata":"https://www.wikidata.org/wiki/Q82642","display_name":"Blood pressure","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[{"descriptor_ui":"D000098415","descriptor_name":"Convolutional Neural Networks","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000098415","descriptor_name":"Convolutional Neural Networks","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000098415","descriptor_name":"Convolutional Neural Networks","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003920","descriptor_name":"Diabetes Mellitus","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":true},{"descriptor_ui":"D003920","descriptor_name":"Diabetes Mellitus","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":true},{"descriptor_ui":"D003920","descriptor_name":"Diabetes Mellitus","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":true},{"descriptor_ui":"D003920","descriptor_name":"Diabetes Mellitus","qualifier_ui":"Q000503","qualifier_name":"physiopathology","is_major_topic":true},{"descriptor_ui":"D003920","descriptor_name":"Diabetes Mellitus","qualifier_ui":"Q000503","qualifier_name":"physiopathology","is_major_topic":true},{"descriptor_ui":"D003920","descriptor_name":"Diabetes Mellitus","qualifier_ui":"Q000503","qualifier_name":"physiopathology","is_major_topic":true},{"descriptor_ui":"D003936","descriptor_name":"Diagnosis, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D003936","descriptor_name":"Diagnosis, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D003936","descriptor_name":"Diagnosis, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D004562","descriptor_name":"Electrocardiography","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D004562","descriptor_name":"Electrocardiography","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D004562","descriptor_name":"Electrocardiography","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006339","descriptor_name":"Heart Rate","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D006339","descriptor_name":"Heart Rate","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D006339","descriptor_name":"Heart Rate","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"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":"D008297","descriptor_name":"Male","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008297","descriptor_name":"Male","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008297","descriptor_name":"Male","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012680","descriptor_name":"Sensitivity and Specificity","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012680","descriptor_name":"Sensitivity and Specificity","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012680","descriptor_name":"Sensitivity and Specificity","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D019277","descriptor_name":"Entropy","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D019277","descriptor_name":"Entropy","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D019277","descriptor_name":"Entropy","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.3233/shti250979","is_oa":true,"landing_page_url":"https://doi.org/10.3233/shti250979","pdf_url":null,"source":{"id":"https://openalex.org/S4210179765","display_name":"Studies in health technology and informatics","issn_l":"0926-9630","issn":["0926-9630","1879-8365"],"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":"book series"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Studies in Health Technology and Informatics","raw_type":"book-chapter"},{"id":"pmid:40775997","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40775997","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":"Studies in health technology and informatics","raw_type":"Journal Article"}],"best_oa_location":{"id":"doi:10.3233/shti250979","is_oa":true,"landing_page_url":"https://doi.org/10.3233/shti250979","pdf_url":null,"source":{"id":"https://openalex.org/S4210179765","display_name":"Studies in health technology and informatics","issn_l":"0926-9630","issn":["0926-9630","1879-8365"],"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":"book series"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Studies in Health Technology and Informatics","raw_type":"book-chapter"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.7400000095367432}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4206182164","https://openalex.org/W1952985933","https://openalex.org/W2374354250","https://openalex.org/W3148222271","https://openalex.org/W2578546604","https://openalex.org/W4390572597","https://openalex.org/W2152868608","https://openalex.org/W3104701645","https://openalex.org/W4362659335","https://openalex.org/W2376346938"],"abstract_inverted_index":{"Heart":[0],"Rate":[1],"Variability":[2],"(HRV)":[3],"is":[4,155],"associated":[5],"with":[6,40,127,152,167],"diabetic":[7],"complications.":[8],"This":[9,27],"analysis":[10],"can":[11],"quantify":[12],"changes":[13],"in":[14,25,124,137],"heart":[15],"rate":[16],"variability,":[17],"and":[18,32,67,74,91,117,170],"it":[19],"may":[20],"help":[21],"detect":[22],"early":[23,135,161],"alterations":[24],"diabetes.":[26,141],"study":[28,69],"aimed":[29],"to":[30,100],"design":[31],"validate":[33],"a":[34],"Convolutional":[35],"Neural":[36],"Network":[37],"(CNN)":[38],"empowered":[39],"entropy":[41,75,119,128,153],"metrics":[42,120,154],"(RNC-Rica)":[43],"for":[44,59,159,174],"the":[45,102,118,146,160],"diagnosis":[46,162],"of":[47,70,88,134,140,163],"diabetes":[48,164],"through":[49],"EKG":[50,66],"recordings.":[51],"The":[52,130,142],"RNC-Rica":[53],"model":[54,125,131,150],"thus":[55],"uses":[56],"CNN":[57],"architecture":[58],"two-dimensional":[60],"convolution":[61],"based":[62],"feature":[63],"extraction":[64],"from":[65],"simultaneous":[68],"age,":[71],"HRV":[72],"measures":[73],"measures.":[76],"From":[77],"these":[78],"setups":[79,82],"five":[80],"test":[81],"were":[83],"evaluated":[84],"by":[85],"integrating":[86],"combinations":[87],"convolutional":[89],"layers":[90],"entropy.":[92],"Through":[93],"this":[94],"approach,":[95],"Test":[96],"4":[97],"was":[98,132],"found":[99],"yield":[101],"best":[103],"results":[104,143],"(accuracy:":[105],"70.3%;":[106],"sensitivity:":[107],"78.4%;":[108],"specificity:":[109],"62.0%;":[110],"positive":[111],"predictive":[112],"value:":[113],"68.0%;":[114],"F1-Score:":[115],"72.8%),":[116],"illustrate":[121],"an":[122,156],"improvement":[123],"stability":[126],"metrics.":[129],"capable":[133],"detection":[136],"subclinical":[138],"stages":[139],"indicate":[144],"that":[145],"regularized":[147],"nearest":[148],"centroid-Rica":[149],"augmented":[151],"effective":[157],"tool":[158],"via":[165],"EKG,":[166],"high":[168],"sensitivity,":[169],"also":[171],"statistically":[172],"significant":[173],"clinical":[175],"classification.":[176]},"counts_by_year":[],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}