{"id":"https://openalex.org/W4407028818","doi":"https://doi.org/10.1186/s12911-025-02887-y","title":"Using a robust model to detect the association between anthropometric factors and T2DM: machine learning approaches","display_name":"Using a robust model to detect the association between anthropometric factors and T2DM: machine learning approaches","publication_year":2025,"publication_date":"2025-01-31","ids":{"openalex":"https://openalex.org/W4407028818","doi":"https://doi.org/10.1186/s12911-025-02887-y","pmid":"https://pubmed.ncbi.nlm.nih.gov/39891090"},"language":"en","primary_location":{"id":"doi:10.1186/s12911-025-02887-y","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12911-025-02887-y","pdf_url":"https://bmcmedinformdecismak.biomedcentral.com/counter/pdf/10.1186/s12911-025-02887-y","source":{"id":"https://openalex.org/S107516304","display_name":"BMC Medical Informatics and Decision Making","issn_l":"1472-6947","issn":["1472-6947"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Medical Informatics and Decision Making","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://bmcmedinformdecismak.biomedcentral.com/counter/pdf/10.1186/s12911-025-02887-y","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5020127269","display_name":"Nafiseh Hosseini","orcid":"https://orcid.org/0000-0002-7244-7982"},"institutions":[{"id":"https://openalex.org/I165560825","display_name":"Mashhad University of Medical Sciences","ror":"https://ror.org/04sfka033","country_code":"IR","type":"education","lineage":["https://openalex.org/I165560825"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Nafiseh Hosseini","raw_affiliation_strings":["Department of Medical Informatics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran","International UNESCO Center for Health-Related Basic Sciences and Human Nutrition, Mashhad University of Medical Sciences, Mashhad, 99199-91766, Iran"],"raw_orcid":"https://orcid.org/0000-0002-7244-7982","affiliations":[{"raw_affiliation_string":"Department of Medical Informatics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran","institution_ids":["https://openalex.org/I165560825"]},{"raw_affiliation_string":"International UNESCO Center for Health-Related Basic Sciences and Human Nutrition, Mashhad University of Medical Sciences, Mashhad, 99199-91766, Iran","institution_ids":["https://openalex.org/I165560825"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047477627","display_name":"Hamid Tanzadehpanah","orcid":"https://orcid.org/0000-0002-1711-5619"},"institutions":[{"id":"https://openalex.org/I165560825","display_name":"Mashhad University of Medical Sciences","ror":"https://ror.org/04sfka033","country_code":"IR","type":"education","lineage":["https://openalex.org/I165560825"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Hamid Tanzadehpanah","raw_affiliation_strings":["Antimicrobial Resistance Research Center, Mashhad University of Medical Sciences, Mashhad, Iran","Basic Sciences Research Institute, Mashhad University of Medical Sciences, Mashhad, Iran","Metabolic Syndrome Research Center, Mashhad University of Medical Sciences, Mashhad, Iran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Antimicrobial Resistance Research Center, Mashhad University of Medical Sciences, Mashhad, Iran","institution_ids":["https://openalex.org/I165560825"]},{"raw_affiliation_string":"Basic Sciences Research Institute, Mashhad University of Medical Sciences, Mashhad, Iran","institution_ids":["https://openalex.org/I165560825"]},{"raw_affiliation_string":"Metabolic Syndrome Research Center, Mashhad University of Medical Sciences, Mashhad, Iran","institution_ids":["https://openalex.org/I165560825"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065229030","display_name":"Amin Mansoori","orcid":"https://orcid.org/0000-0003-4442-3358"},"institutions":[{"id":"https://openalex.org/I86958956","display_name":"Ferdowsi University of Mashhad","ror":"https://ror.org/00g6ka752","country_code":"IR","type":"education","lineage":["https://openalex.org/I86958956"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Amin Mansoori","raw_affiliation_strings":["Department of Applied Mathematics, School of Mathematical Sciences, Ferdowsi University of Mashhad, Mashhad, Iran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Applied Mathematics, School of Mathematical Sciences, Ferdowsi University of Mashhad, Mashhad, Iran","institution_ids":["https://openalex.org/I86958956"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042422813","display_name":"Mostafa Sabzekar","orcid":"https://orcid.org/0000-0002-6886-1240"},"institutions":[{"id":"https://openalex.org/I97626857","display_name":"University of Birjand","ror":"https://ror.org/03g4hym73","country_code":"IR","type":"education","lineage":["https://openalex.org/I97626857"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Mostafa Sabzekar","raw_affiliation_strings":["Department of Computer Engineering, Birjand University of Technology, Birjand, Iran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Birjand University of Technology, Birjand, Iran","institution_ids":["https://openalex.org/I97626857"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102927546","display_name":"Gordon A. Ferns","orcid":null},"institutions":[{"id":"https://openalex.org/I100063501","display_name":"Brighton and Sussex Medical School","ror":"https://ror.org/01qz7fr76","country_code":"GB","type":"education","lineage":["https://openalex.org/I100063501","https://openalex.org/I162608824","https://openalex.org/I71637028"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Gordon A. Ferns","raw_affiliation_strings":["Brighton and Sussex Medical School, Division of Medical Education, Brighton, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Brighton and Sussex Medical School, Division of Medical Education, Brighton, UK","institution_ids":["https://openalex.org/I100063501"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091574629","display_name":"Habibollah Esmaily","orcid":"https://orcid.org/0000-0003-4139-546X"},"institutions":[{"id":"https://openalex.org/I165560825","display_name":"Mashhad University of Medical Sciences","ror":"https://ror.org/04sfka033","country_code":"IR","type":"education","lineage":["https://openalex.org/I165560825"]}],"countries":["IR"],"is_corresponding":true,"raw_author_name":"Habibollah Esmaily","raw_affiliation_strings":["Department of Biostatistics, School of Health, Mashhad University of Medical Sciences, Mashhad, Iran. esmailyh@mums.ac.ir","Social Determinants of Health Research Center, Mashhad University of Medical Sciences, Mashhad, Iran. esmailyh@mums.ac.ir","Department of Biostatistics, School of Health, Mashhad University of Medical Sciences, Mashhad, Iran","Social Determinants of Health Research Center, Mashhad University of Medical Sciences, Mashhad, Iran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biostatistics, School of Health, Mashhad University of Medical Sciences, Mashhad, Iran. esmailyh@mums.ac.ir","institution_ids":["https://openalex.org/I165560825"]},{"raw_affiliation_string":"Social Determinants of Health Research Center, Mashhad University of Medical Sciences, Mashhad, Iran. esmailyh@mums.ac.ir","institution_ids":["https://openalex.org/I165560825"]},{"raw_affiliation_string":"Department of Biostatistics, School of Health, Mashhad University of Medical Sciences, Mashhad, Iran","institution_ids":["https://openalex.org/I165560825"]},{"raw_affiliation_string":"Social Determinants of Health Research Center, Mashhad University of Medical Sciences, Mashhad, Iran","institution_ids":["https://openalex.org/I165560825"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113393752","display_name":"Majid Ghayour-Mobarhan","orcid":null},"institutions":[{"id":"https://openalex.org/I165560825","display_name":"Mashhad University of Medical Sciences","ror":"https://ror.org/04sfka033","country_code":"IR","type":"education","lineage":["https://openalex.org/I165560825"]}],"countries":["IR"],"is_corresponding":true,"raw_author_name":"Majid Ghayour-Mobarhan","raw_affiliation_strings":["International UNESCO Center for Health-Related Basic Sciences and Human Nutrition, Mashhad University of Medical Sciences, Mashhad, 99199-91766, Iran. ghayourm@mums.ac.ir","Metabolic Syndrome Research Center, Mashhad University of Medical Sciences, Mashhad, Iran. ghayourm@mums.ac.ir","International UNESCO Center for Health-Related Basic Sciences and Human Nutrition, Mashhad University of Medical Sciences, Mashhad, 99199-91766, Iran","Metabolic Syndrome Research Center, Mashhad University of Medical Sciences, Mashhad, Iran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"International UNESCO Center for Health-Related Basic Sciences and Human Nutrition, Mashhad University of Medical Sciences, Mashhad, 99199-91766, Iran. ghayourm@mums.ac.ir","institution_ids":["https://openalex.org/I165560825"]},{"raw_affiliation_string":"Metabolic Syndrome Research Center, Mashhad University of Medical Sciences, Mashhad, Iran. ghayourm@mums.ac.ir","institution_ids":["https://openalex.org/I165560825"]},{"raw_affiliation_string":"International UNESCO Center for Health-Related Basic Sciences and Human Nutrition, Mashhad University of Medical Sciences, Mashhad, 99199-91766, Iran","institution_ids":["https://openalex.org/I165560825"]},{"raw_affiliation_string":"Metabolic Syndrome Research Center, Mashhad University of Medical Sciences, Mashhad, Iran","institution_ids":["https://openalex.org/I165560825"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5091574629","https://openalex.org/A5113393752"],"corresponding_institution_ids":["https://openalex.org/I165560825"],"apc_list":{"value":2690,"currency":"USD","value_usd":2690},"apc_paid":{"value":2690,"currency":"USD","value_usd":2690},"fwci":3.1195,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.90686638,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"25","issue":"1","first_page":"49","last_page":"49"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12279","display_name":"Body Composition Measurement Techniques","score":0.23029999434947968,"subfield":{"id":"https://openalex.org/subfields/2737","display_name":"Physiology"},"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/T12279","display_name":"Body Composition Measurement Techniques","score":0.23029999434947968,"subfield":{"id":"https://openalex.org/subfields/2737","display_name":"Physiology"},"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/T10397","display_name":"Nutrition and Health in Aging","score":0.18119999766349792,"subfield":{"id":"https://openalex.org/subfields/2737","display_name":"Physiology"},"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/T10821","display_name":"Cardiovascular Function and Risk Factors","score":0.14180000126361847,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/health-informatics","display_name":"Health informatics","score":0.7902724742889404},{"id":"https://openalex.org/keywords/anthropometry","display_name":"Anthropometry","score":0.6589998006820679},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6346899271011353},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5568163990974426},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5223649144172668},{"id":"https://openalex.org/keywords/association","display_name":"Association (psychology)","score":0.4248390793800354},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.20593735575675964},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.1271093487739563},{"id":"https://openalex.org/keywords/public-health","display_name":"Public health","score":0.1267680525779724},{"id":"https://openalex.org/keywords/nursing","display_name":"Nursing","score":0.060825347900390625},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.059396892786026}],"concepts":[{"id":"https://openalex.org/C145642194","wikidata":"https://www.wikidata.org/wiki/Q870895","display_name":"Health informatics","level":3,"score":0.7902724742889404},{"id":"https://openalex.org/C61427482","wikidata":"https://www.wikidata.org/wiki/Q6656244","display_name":"Anthropometry","level":2,"score":0.6589998006820679},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6346899271011353},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5568163990974426},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5223649144172668},{"id":"https://openalex.org/C142853389","wikidata":"https://www.wikidata.org/wiki/Q744778","display_name":"Association (psychology)","level":2,"score":0.4248390793800354},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.20593735575675964},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.1271093487739563},{"id":"https://openalex.org/C138816342","wikidata":"https://www.wikidata.org/wiki/Q189603","display_name":"Public health","level":2,"score":0.1267680525779724},{"id":"https://openalex.org/C159110408","wikidata":"https://www.wikidata.org/wiki/Q121176","display_name":"Nursing","level":1,"score":0.060825347900390625},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.059396892786026},{"id":"https://openalex.org/C542102704","wikidata":"https://www.wikidata.org/wiki/Q183257","display_name":"Psychotherapist","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000328","descriptor_name":"Adult","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000328","descriptor_name":"Adult","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000328","descriptor_name":"Adult","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000328","descriptor_name":"Adult","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000328","descriptor_name":"Adult","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000368","descriptor_name":"Aged","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000368","descriptor_name":"Aged","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000368","descriptor_name":"Aged","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000368","descriptor_name":"Aged","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000368","descriptor_name":"Aged","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000886","descriptor_name":"Anthropometry","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000886","descriptor_name":"Anthropometry","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000886","descriptor_name":"Anthropometry","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000886","descriptor_name":"Anthropometry","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000886","descriptor_name":"Anthropometry","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003924","descriptor_name":"Diabetes Mellitus, Type 2","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D003924","descriptor_name":"Diabetes Mellitus, Type 2","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D003924","descriptor_name":"Diabetes Mellitus, Type 2","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":true},{"descriptor_ui":"D003924","descriptor_name":"Diabetes Mellitus, Type 2","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":true},{"descriptor_ui":"D003924","descriptor_name":"Diabetes Mellitus, Type 2","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":true},{"descriptor_ui":"D003924","descriptor_name":"Diabetes Mellitus, Type 2","qualifier_ui":"Q000453","qualifier_name":"epidemiology","is_major_topic":true},{"descriptor_ui":"D003924","descriptor_name":"Diabetes Mellitus, Type 2","qualifier_ui":"Q000453","qualifier_name":"epidemiology","is_major_topic":true},{"descriptor_ui":"D003924","descriptor_name":"Diabetes Mellitus, Type 2","qualifier_ui":"Q000453","qualifier_name":"epidemiology","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":"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":"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":"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":"D007492","descriptor_name":"Iran","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007492","descriptor_name":"Iran","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":"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":"D008875","descriptor_name":"Middle Aged","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008875","descriptor_name":"Middle Aged","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008875","descriptor_name":"Middle Aged","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015992","descriptor_name":"Body Mass Index","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015992","descriptor_name":"Body Mass Index","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015992","descriptor_name":"Body Mass Index","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015992","descriptor_name":"Body Mass Index","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015992","descriptor_name":"Body Mass Index","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":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","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":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","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":false},{"descriptor_ui":"D060388","descriptor_name":"Support Vector Machine","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D060388","descriptor_name":"Support Vector Machine","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":5,"locations":[{"id":"doi:10.1186/s12911-025-02887-y","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12911-025-02887-y","pdf_url":"https://bmcmedinformdecismak.biomedcentral.com/counter/pdf/10.1186/s12911-025-02887-y","source":{"id":"https://openalex.org/S107516304","display_name":"BMC Medical Informatics and Decision Making","issn_l":"1472-6947","issn":["1472-6947"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Medical Informatics and Decision Making","raw_type":"journal-article"},{"id":"pmid:39891090","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/39891090","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":"BMC medical informatics and decision making","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:11786328","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11786328","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11786328/pdf/12911_2025_Article_2887.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"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":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"BMC Med Inform Decis Mak","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:8184144786cc47fb844d26ba9807d5a2","is_oa":true,"landing_page_url":"https://doaj.org/article/8184144786cc47fb844d26ba9807d5a2","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":"BMC Medical Informatics and Decision Making, Vol 25, Iss 1, Pp 1-10 (2025)","raw_type":"article"},{"id":"pmh:oai:figshare.com:article/29236403","is_oa":true,"landing_page_url":"https://figshare.com/articles/journal_contribution/Using_a_robust_model_to_detect_the_association_between_anthropometric_factors_and_T2DM_machine_learning_approaches/29236403","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1186/s12911-025-02887-y","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12911-025-02887-y","pdf_url":"https://bmcmedinformdecismak.biomedcentral.com/counter/pdf/10.1186/s12911-025-02887-y","source":{"id":"https://openalex.org/S107516304","display_name":"BMC Medical Informatics and Decision Making","issn_l":"1472-6947","issn":["1472-6947"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Medical Informatics and Decision Making","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4407028818.pdf","grobid_xml":"https://content.openalex.org/works/W4407028818.grobid-xml"},"referenced_works_count":46,"referenced_works":["https://openalex.org/W1750092950","https://openalex.org/W1977947448","https://openalex.org/W2025647920","https://openalex.org/W2103522741","https://openalex.org/W2118414527","https://openalex.org/W2129648876","https://openalex.org/W2188829624","https://openalex.org/W2775450699","https://openalex.org/W2795995848","https://openalex.org/W2900329012","https://openalex.org/W2953421802","https://openalex.org/W2981132624","https://openalex.org/W2994732610","https://openalex.org/W3017209650","https://openalex.org/W3092374138","https://openalex.org/W3106102469","https://openalex.org/W3126599133","https://openalex.org/W3130449168","https://openalex.org/W3135225825","https://openalex.org/W3179092643","https://openalex.org/W3185246067","https://openalex.org/W4205426671","https://openalex.org/W4207004849","https://openalex.org/W4213430288","https://openalex.org/W4224122349","https://openalex.org/W4224233009","https://openalex.org/W4229457591","https://openalex.org/W4281953337","https://openalex.org/W4285218362","https://openalex.org/W4295338724","https://openalex.org/W4301180893","https://openalex.org/W4311220700","https://openalex.org/W4315928031","https://openalex.org/W4318483790","https://openalex.org/W4320900840","https://openalex.org/W4322501840","https://openalex.org/W4376288575","https://openalex.org/W4377094175","https://openalex.org/W4379196941","https://openalex.org/W4380357843","https://openalex.org/W4383501340","https://openalex.org/W4384025344","https://openalex.org/W4385513920","https://openalex.org/W4387048352","https://openalex.org/W4387414035","https://openalex.org/W4387950599"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W3046775127","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474"],"abstract_inverted_index":{"BACKGROUND:":[0],"The":[1,93,105,118,196,208,225,240,252],"aim":[2],"of":[3,50,65,120,198,212,247,290,298],"this":[4],"study":[5,39],"was":[6,60,82,95,124,202,217,232],"to":[7,12,84,189],"evaluate":[8],"the":[9,14,31,63,86,121,169,191,199,215,221,228,244,248,262,270,281,288,291,296],"potential":[10],"models":[11,249],"determine":[13],"most":[15],"important":[16],"anthropometric":[17,67,265],"factors":[18,68,146,176,184,266],"associated":[19],"with":[20,126,194],"type":[21],"2":[22],"diabetes":[23],"mellitus":[24],"(T2DM).":[25],"METHOD:":[26],"A":[27,77],"dataset":[28],"derived":[29],"from":[30],"Mashhad":[32],"Stroke":[33],"and":[34,54,69,90,102,111,131,142,174,179,182,236,267,294],"heart":[35],"atherosclerotic":[36],"disorders":[37],"(MASHAD)":[38],"comprising":[40],"9354":[41],"subject":[42],"aged":[43],"65":[44],"-":[45],"35.":[46],"25%":[47],"(2336":[48],"people)":[49,57],"subjects":[51],"were":[52,72,115,166,187],"diabetic":[53],"75%":[55],"(7018":[56],"where":[58],"non-diabetic":[59],"used":[61,83,167],"for":[62,205,214,234,238,260],"analysis":[64,114,141,286],"10":[66],"age":[70],"that":[71],"measured":[73],"in":[74,168,177,185],"all":[75],"patients.":[76],"K-nearest":[78],"neighbor":[79],"(KNN)":[80],"model":[81,94,123,201,216,242,254,293],"assess":[85],"association":[87,193,263],"between":[88,264],"T2DM":[89],"selected":[91],"factors.":[92],"evaluated":[96],"using":[97],"accuracy,":[98],"sensitivity,":[99],"specificity,":[100],"precision":[101],"f1-measure":[103],"parameters.":[104],"receiver":[106],"operating":[107],"characteristic":[108],"(ROC)":[109],"curve":[110,230],"factor":[112],"importance":[113],"also":[116],"determined.":[117],"performance":[119],"KNN":[122,200,241,253,292],"compared":[125],"Artificial":[127],"neural":[128],"network":[129],"(ANN)":[130],"support":[132],"vector":[133],"machine":[134],"(SVM)":[135],"models.":[136],"RESULT:":[137],"After":[138],"feature":[139],"selection":[140,285],"assessing":[143],"multicollinearity,":[144],"six":[145],"(Mid-arm":[147],"Circumference":[148,151],"(MAC),":[149],"Waist":[150],"(WC),":[152],"Body":[153,157,161],"Roundness":[154],"Index":[155,159,163],"(BRI),":[156],"Adiposity":[158],"(BAI),":[160],"Mass":[162],"(BMI),":[164],"age)":[165],"final":[170,299],"model.":[171],"BRI,":[172,181],"BAI":[173],"MAC":[175,183],"males":[178],"BMI,":[180],"females":[186],"found":[188],"have":[190],"greatest":[192],"T2DM.":[195,268],"accuracy":[197,258,297],"approximately":[203],"93%":[204],"both":[206],"genders.":[207],"best":[209,245],"K":[210,271],"(number":[211],"neighbors)":[213],"4":[218],"which":[219],"had":[220,255],"lowest":[222],"error":[223,282],"rate.":[224,283],"area":[226],"under":[227],"ROC":[229],"(AUC)":[231],"0.985":[233],"men":[235],"0.986":[237],"women.":[239],"achieved":[243],"result":[246],"explored.":[250],"CONCLUSION:":[251],"a":[256],"high":[257],"(93%)":[259],"predicting":[261],"Selecting":[269],"parameter":[272],"(nearest":[273],"neighbor)":[274],"has":[275],"an":[276],"essential":[277],"impact":[278],"on":[279],"reducing":[280],"Feature":[284],"reduces":[287],"dimensions":[289],"increases":[295],"results.":[300]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3}],"updated_date":"2026-08-10T07:06:39.071514","created_date":"2025-10-10T00:00:00"}