{"id":"https://openalex.org/W4399581535","doi":"https://doi.org/10.3389/frai.2024.1355287","title":"Developing and comparing deep learning and machine learning algorithms for osteoporosis risk prediction","display_name":"Developing and comparing deep learning and machine learning algorithms for osteoporosis risk prediction","publication_year":2024,"publication_date":"2024-06-11","ids":{"openalex":"https://openalex.org/W4399581535","doi":"https://doi.org/10.3389/frai.2024.1355287","pmid":"https://pubmed.ncbi.nlm.nih.gov/38919268"},"language":"en","primary_location":{"id":"doi:10.3389/frai.2024.1355287","is_oa":true,"landing_page_url":"https://doi.org/10.3389/frai.2024.1355287","pdf_url":"https://www.frontiersin.org/articles/10.3389/frai.2024.1355287/pdf?isPublishedV2=False","source":{"id":"https://openalex.org/S4210197006","display_name":"Frontiers in Artificial Intelligence","issn_l":"2624-8212","issn":["2624-8212"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.frontiersin.org/articles/10.3389/frai.2024.1355287/pdf?isPublishedV2=False","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5028456676","display_name":"Chuan Qiu","orcid":"https://orcid.org/0000-0001-6202-9229"},"institutions":[{"id":"https://openalex.org/I114832834","display_name":"Tulane University","ror":"https://ror.org/04vmvtb21","country_code":"US","type":"education","lineage":["https://openalex.org/I114832834"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chuan Qiu","raw_affiliation_strings":["Tulane Center for Biomedical Informatics and Genomics, Deming Department of Medicine, School of Medicine, Tulane University, New Orleans, LA, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tulane Center for Biomedical Informatics and Genomics, Deming Department of Medicine, School of Medicine, Tulane University, New Orleans, LA, United States","institution_ids":["https://openalex.org/I114832834"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112982449","display_name":"Kuan\u2010Jui Su","orcid":null},"institutions":[{"id":"https://openalex.org/I114832834","display_name":"Tulane University","ror":"https://ror.org/04vmvtb21","country_code":"US","type":"education","lineage":["https://openalex.org/I114832834"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kuanjui Su","raw_affiliation_strings":["Tulane Center for Biomedical Informatics and Genomics, Deming Department of Medicine, School of Medicine, Tulane University, New Orleans, LA, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tulane Center for Biomedical Informatics and Genomics, Deming Department of Medicine, School of Medicine, Tulane University, New Orleans, LA, United States","institution_ids":["https://openalex.org/I114832834"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100631895","display_name":"Zhe Luo","orcid":"https://orcid.org/0000-0002-6800-5356"},"institutions":[{"id":"https://openalex.org/I114832834","display_name":"Tulane University","ror":"https://ror.org/04vmvtb21","country_code":"US","type":"education","lineage":["https://openalex.org/I114832834"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhe Luo","raw_affiliation_strings":["Tulane Center for Biomedical Informatics and Genomics, Deming Department of Medicine, School of Medicine, Tulane University, New Orleans, LA, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tulane Center for Biomedical Informatics and Genomics, Deming Department of Medicine, School of Medicine, Tulane University, New Orleans, LA, United States","institution_ids":["https://openalex.org/I114832834"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100627660","display_name":"Qing Tian","orcid":"https://orcid.org/0000-0003-1808-2887"},"institutions":[{"id":"https://openalex.org/I114832834","display_name":"Tulane University","ror":"https://ror.org/04vmvtb21","country_code":"US","type":"education","lineage":["https://openalex.org/I114832834"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qing Tian","raw_affiliation_strings":["Tulane Center for Biomedical Informatics and Genomics, Deming Department of Medicine, School of Medicine, Tulane University, New Orleans, LA, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tulane Center for Biomedical Informatics and Genomics, Deming Department of Medicine, School of Medicine, Tulane University, New Orleans, LA, United States","institution_ids":["https://openalex.org/I114832834"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103049380","display_name":"Lan\u2010Juan Zhao","orcid":"https://orcid.org/0000-0001-6342-2495"},"institutions":[{"id":"https://openalex.org/I114832834","display_name":"Tulane University","ror":"https://ror.org/04vmvtb21","country_code":"US","type":"education","lineage":["https://openalex.org/I114832834"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lanjuan Zhao","raw_affiliation_strings":["Tulane Center for Biomedical Informatics and Genomics, Deming Department of Medicine, School of Medicine, Tulane University, New Orleans, LA, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tulane Center for Biomedical Informatics and Genomics, Deming Department of Medicine, School of Medicine, Tulane University, New Orleans, LA, United States","institution_ids":["https://openalex.org/I114832834"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101377550","display_name":"Li Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I114832834","display_name":"Tulane University","ror":"https://ror.org/04vmvtb21","country_code":"US","type":"education","lineage":["https://openalex.org/I114832834"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Li Wu","raw_affiliation_strings":["Tulane Center for Biomedical Informatics and Genomics, Deming Department of Medicine, School of Medicine, Tulane University, New Orleans, LA, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tulane Center for Biomedical Informatics and Genomics, Deming Department of Medicine, School of Medicine, Tulane University, New Orleans, LA, United States","institution_ids":["https://openalex.org/I114832834"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024194480","display_name":"Hong\u2010Wen Deng","orcid":"https://orcid.org/0000-0002-0387-8818"},"institutions":[{"id":"https://openalex.org/I114832834","display_name":"Tulane University","ror":"https://ror.org/04vmvtb21","country_code":"US","type":"education","lineage":["https://openalex.org/I114832834"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Hongwen Deng","raw_affiliation_strings":["Tulane Center for Biomedical Informatics and Genomics, Deming Department of Medicine, School of Medicine, Tulane University, New Orleans, LA, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tulane Center for Biomedical Informatics and Genomics, Deming Department of Medicine, School of Medicine, Tulane University, New Orleans, LA, United States","institution_ids":["https://openalex.org/I114832834"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002208932","display_name":"Hui Shen","orcid":"https://orcid.org/0000-0002-5582-4555"},"institutions":[{"id":"https://openalex.org/I114832834","display_name":"Tulane University","ror":"https://ror.org/04vmvtb21","country_code":"US","type":"education","lineage":["https://openalex.org/I114832834"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Hui Shen","raw_affiliation_strings":["Tulane Center for Biomedical Informatics and Genomics, Deming Department of Medicine, School of Medicine, Tulane University, New Orleans, LA, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tulane Center for Biomedical Informatics and Genomics, Deming Department of Medicine, School of Medicine, Tulane University, New Orleans, LA, United States","institution_ids":["https://openalex.org/I114832834"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5002208932","https://openalex.org/A5024194480"],"corresponding_institution_ids":["https://openalex.org/I114832834"],"apc_list":{"value":1150,"currency":"USD","value_usd":1150},"apc_paid":{"value":1150,"currency":"USD","value_usd":1150},"fwci":7.6253,"has_fulltext":true,"cited_by_count":17,"citation_normalized_percentile":{"value":0.98239899,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"7","issue":null,"first_page":"1355287","last_page":"1355287"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10071","display_name":"Bone health and osteoporosis research","score":0.7674000263214111,"subfield":{"id":"https://openalex.org/subfields/2732","display_name":"Orthopedics and Sports 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/T10071","display_name":"Bone health and osteoporosis research","score":0.7674000263214111,"subfield":{"id":"https://openalex.org/subfields/2732","display_name":"Orthopedics and Sports 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/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.03759999945759773,"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.028999999165534973,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"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/machine-learning","display_name":"Machine learning","score":0.6506382822990417},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6051807403564453},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.583188533782959},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.45474809408187866},{"id":"https://openalex.org/keywords/osteoporosis","display_name":"Osteoporosis","score":0.4310101568698883},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.42875584959983826},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.18025076389312744},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.07907834649085999}],"concepts":[{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6506382822990417},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6051807403564453},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.583188533782959},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.45474809408187866},{"id":"https://openalex.org/C2776541429","wikidata":"https://www.wikidata.org/wiki/Q165328","display_name":"Osteoporosis","level":2,"score":0.4310101568698883},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.42875584959983826},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.18025076389312744},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.07907834649085999}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3389/frai.2024.1355287","is_oa":true,"landing_page_url":"https://doi.org/10.3389/frai.2024.1355287","pdf_url":"https://www.frontiersin.org/articles/10.3389/frai.2024.1355287/pdf?isPublishedV2=False","source":{"id":"https://openalex.org/S4210197006","display_name":"Frontiers in Artificial Intelligence","issn_l":"2624-8212","issn":["2624-8212"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence","raw_type":"journal-article"},{"id":"pmid:38919268","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/38919268","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":"Frontiers in artificial intelligence","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:11196804","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11196804","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11196804/pdf/frai-07-1355287.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","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Front Artif Intell","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:7743ac8d0c60489782f7fd71a9bbd979","is_oa":false,"landing_page_url":"https://doaj.org/article/7743ac8d0c60489782f7fd71a9bbd979","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Frontiers in Artificial Intelligence, Vol 7 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3389/frai.2024.1355287","is_oa":true,"landing_page_url":"https://doi.org/10.3389/frai.2024.1355287","pdf_url":"https://www.frontiersin.org/articles/10.3389/frai.2024.1355287/pdf?isPublishedV2=False","source":{"id":"https://openalex.org/S4210197006","display_name":"Frontiers in Artificial Intelligence","issn_l":"2624-8212","issn":["2624-8212"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.4699999988079071,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G3602326532","display_name":null,"funder_award_id":"U19AG055373","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G5393102884","display_name":null,"funder_award_id":"R01AR069055","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G5535211269","display_name":null,"funder_award_id":"R01AG061917","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"}],"funders":[{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4399581535.pdf"},"referenced_works_count":66,"referenced_works":["https://openalex.org/W146900863","https://openalex.org/W180102944","https://openalex.org/W1516549389","https://openalex.org/W1606867770","https://openalex.org/W1869175042","https://openalex.org/W1901616594","https://openalex.org/W1975244016","https://openalex.org/W1976415200","https://openalex.org/W1981384212","https://openalex.org/W1981976602","https://openalex.org/W2002599840","https://openalex.org/W2009740511","https://openalex.org/W2011505056","https://openalex.org/W2019935401","https://openalex.org/W2024916097","https://openalex.org/W2035756448","https://openalex.org/W2042304149","https://openalex.org/W2049097764","https://openalex.org/W2049295438","https://openalex.org/W2053389701","https://openalex.org/W2058854776","https://openalex.org/W2067658292","https://openalex.org/W2072662858","https://openalex.org/W2086532532","https://openalex.org/W2087141873","https://openalex.org/W2087899382","https://openalex.org/W2096352448","https://openalex.org/W2114060717","https://openalex.org/W2115884121","https://openalex.org/W2118978333","https://openalex.org/W2119387367","https://openalex.org/W2121289914","https://openalex.org/W2134734587","https://openalex.org/W2136598250","https://openalex.org/W2141875544","https://openalex.org/W2145718160","https://openalex.org/W2153723630","https://openalex.org/W2160815625","https://openalex.org/W2168301815","https://openalex.org/W2170330011","https://openalex.org/W2172270209","https://openalex.org/W2264017649","https://openalex.org/W2311607323","https://openalex.org/W2345512687","https://openalex.org/W2442147102","https://openalex.org/W2502949459","https://openalex.org/W2562319768","https://openalex.org/W2590147570","https://openalex.org/W2618530766","https://openalex.org/W2752747624","https://openalex.org/W2796809202","https://openalex.org/W2809443489","https://openalex.org/W2902433159","https://openalex.org/W2919115771","https://openalex.org/W2922930052","https://openalex.org/W2952230511","https://openalex.org/W2961871611","https://openalex.org/W3005910971","https://openalex.org/W4296810518","https://openalex.org/W4327715646","https://openalex.org/W4362559128","https://openalex.org/W4392372590","https://openalex.org/W6680285999","https://openalex.org/W6682646779","https://openalex.org/W6683738474","https://openalex.org/W6718222771"],"related_works":["https://openalex.org/W2731899572","https://openalex.org/W2961085424","https://openalex.org/W3215138031","https://openalex.org/W4306674287","https://openalex.org/W3009238340","https://openalex.org/W4321369474","https://openalex.org/W4360585206","https://openalex.org/W4285208911","https://openalex.org/W3046775127","https://openalex.org/W3082895349"],"abstract_inverted_index":{"Introduction:":[0],"Osteoporosis,":[1],"characterized":[2],"by":[3,174,237,298],"low":[4,40],"bone":[5],"mineral":[6],"density":[7],"(BMD),":[8],"is":[9],"an":[10,350],"increasingly":[11],"serious":[12],"public":[13],"health":[14],"issue.":[15],"So":[16],"far,":[17],"several":[18],"traditional":[19,162],"regression":[20,163],"models":[21,36],"and":[22,96,99,119,129,153,181,211,256,274,356],"machine":[23,156],"learning":[24,48],"(ML)":[25],"algorithms":[26],"have":[27,37],"been":[28],"proposed":[29,46],"for":[30,125,307,353],"predicting":[31,126],"osteoporosis":[32,88,127,134,166,205,308,359],"risk.":[33],"However,":[34],"these":[35,281],"shown":[38],"relatively":[39],"accuracy":[41],"in":[42,87,133,203,360],"clinical":[43,101],"implementation.":[44],"Recently":[45],"deep":[47,53],"(DL)":[49],"approaches,":[50],"such":[51],"as":[52,158,160],"neural":[54,147],"network":[55,148],"(DNN),":[56],"which":[57,345],"can":[58,82,315],"discover":[59],"knowledge":[60],"from":[61,111],"complex":[62],"hidden":[63],"interactions,":[64],"offer":[65],"a":[66,84,121,161,318,341],"new":[67],"opportunity":[68],"to":[69,78,221,264,330,348],"improve":[70],"predictive":[71,198,278,320],"performance.":[72],"In":[73,337],"this":[74],"study,":[75],"we":[76,117,189,260,285,339],"aimed":[77],"assess":[79,265],"whether":[80],"DNN":[81,123,193,239,289,313,343],"achieve":[83,317],"better":[85],"performance":[86,132,171,199,279,321],"risk":[89,128,135,213,309],"prediction.":[90,310],"Methods:":[91],"By":[92,184],"utilizing":[93,299],"hip":[94],"BMD":[95,207,215],"extensive":[97],"demographic":[98],"routine":[100],"data":[102],"of":[103,268,271,280,332,358],"8,134":[104],"subjects":[105],"with":[106,137],"age":[107],"more":[108],"than":[109],"40":[110],"the":[112,192,196,222,230,238,266,277,288,301,312,333,361],"Louisiana":[113],"Osteoporosis":[114],"Study":[115],"(LOS),":[116],"developed":[118,340],"constructed":[120],"novel":[122,342],"framework":[124],"compared":[130,220],"its":[131],"prediction":[136],"four":[138],"conventional":[139],"ML":[140],"models,":[141],"namely":[142],"random":[143],"forest":[144],"(RF),":[145],"artificial":[146],"(ANN),":[149],"k-nearest":[150],"neighbor":[151],"(KNN),":[152],"support":[154],"vector":[155],"(SVM),":[157],"well":[159,293],"model":[164,240,290,314,344],"termed":[165],"self-assessment":[167],"tool":[168],"(OST).":[169],"Model":[170],"was":[172,328,346],"assessed":[173],"area":[175],"under":[176],"'receiver":[177],"operating":[178],"curve'":[179],"(AUC)":[180],"accuracy.":[182],"Results:":[183],"using":[185],"16":[186],"discriminative":[187],"variables,":[188],"observed":[190,286],"that":[191,229,287],"approach":[194],"achieved":[195],"best":[197],"(AUC":[200,294,322],"=":[201,295,323],"0.848)":[202],"classifying":[204],"(hip":[206,214],"T-score":[208,216],"\u2264":[209],"-1.0)":[210,218],"non-osteoporosis":[212],">":[217],"subjects,":[219],"other":[223],"approaches.":[224],"Feature":[225],"importance":[226],"analysis":[227,263],"showed":[228],"top":[231,302],"10":[232,303],"most":[233,304],"important":[234,305],"variables":[235,275,306],"identified":[236],"were":[241],"weight,":[242],"age,":[243],"gender,":[244],"grip":[245],"strength,":[246],"height,":[247],"beer":[248],"drinking,":[249,253],"diastolic":[250],"pressure,":[251],"alcohol":[252],"smoke":[254],"years,":[255],"economic":[257],"level.":[258],"Furthermore,":[259],"performed":[261,291],"subsampling":[262],"effects":[267],"varying":[269],"number":[270],"sample":[272,326],"size":[273,327],"on":[276],"tested":[282],"models.":[283],"Notably,":[284],"equally":[292],"0.846)":[296],"even":[297],"only":[300],"Meanwhile,":[311],"still":[316],"high":[319],"0.826)":[324],"when":[325],"reduced":[329],"50%":[331],"original":[334],"dataset.":[335],"Conclusion:":[336],"conclusion,":[338],"considered":[347],"be":[349],"effective":[351],"algorithm":[352],"early":[354],"diagnosis":[355],"intervention":[357],"aging":[362],"population.":[363]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":15},{"year":2024,"cited_by_count":1}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}