{"id":"https://openalex.org/W4414425760","doi":"https://doi.org/10.1007/s10278-025-01670-9","title":"Comparative Evaluation of Radiomics and Deep Learning Models for Disease Detection in Chest Radiography","display_name":"Comparative Evaluation of Radiomics and Deep Learning Models for Disease Detection in Chest Radiography","publication_year":2025,"publication_date":"2025-09-23","ids":{"openalex":"https://openalex.org/W4414425760","doi":"https://doi.org/10.1007/s10278-025-01670-9","pmid":"https://pubmed.ncbi.nlm.nih.gov/40986191"},"language":"en","primary_location":{"id":"doi:10.1007/s10278-025-01670-9","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10278-025-01670-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10278-025-01670-9.pdf","source":{"id":"https://openalex.org/S62275304","display_name":"Journal of Imaging Informatics in Medicine","issn_l":"0897-1889","issn":["0897-1889","1618-727X","2948-2925","2948-2933"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Imaging Informatics in Medicine","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s10278-025-01670-9.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102070032","display_name":"Zhijin He","orcid":null},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhijin He","raw_affiliation_strings":["Department of Radiology, University of Wisconsin-Madison, Madison, WI, USA","Department of Statistics, University of Wisconsin-Madison, Madison, WI, USA"],"raw_orcid":"https://orcid.org/0009-0000-5756-0840","affiliations":[{"raw_affiliation_string":"Department of Radiology, University of Wisconsin-Madison, Madison, WI, USA","institution_ids":["https://openalex.org/I135310074"]},{"raw_affiliation_string":"Department of Statistics, University of Wisconsin-Madison, Madison, WI, USA","institution_ids":["https://openalex.org/I135310074"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080493254","display_name":"Alan B. McMillan","orcid":"https://orcid.org/0000-0003-4502-6522"},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Alan B. McMillan","raw_affiliation_strings":["Department of Radiology, University of Wisconsin-Madison, Madison, WI, USA. abmcmillan@wisc.edu","Department of Radiology, University of Wisconsin-Madison, Madison, WI, USA"],"raw_orcid":"https://orcid.org/0000-0003-4502-6522","affiliations":[{"raw_affiliation_string":"Department of Radiology, University of Wisconsin-Madison, Madison, WI, USA. abmcmillan@wisc.edu","institution_ids":["https://openalex.org/I135310074"]},{"raw_affiliation_string":"Department of Radiology, University of Wisconsin-Madison, Madison, WI, USA","institution_ids":["https://openalex.org/I135310074"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5080493254"],"corresponding_institution_ids":["https://openalex.org/I135310074"],"apc_list":{"value":4190,"currency":"USD","value_usd":4190},"apc_paid":{"value":4190,"currency":"USD","value_usd":4190},"fwci":4.4326,"has_fulltext":true,"cited_by_count":7,"citation_normalized_percentile":{"value":0.9525335,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"39","issue":"3","first_page":"2340","last_page":"2351"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"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/T10202","display_name":"Lung Cancer Diagnosis and Treatment","score":0.9828000068664551,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory 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/deep-learning","display_name":"Deep learning","score":0.817799985408783},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5974000096321106},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5059999823570251},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.4903999865055084},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.43650001287460327},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.38040000200271606},{"id":"https://openalex.org/keywords/radiomics","display_name":"Radiomics","score":0.34769999980926514},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.3452000021934509}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8464999794960022},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.817799985408783},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.7075999975204468},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5974000096321106},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5527999997138977},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5059999823570251},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.4903999865055084},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.43650001287460327},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.38040000200271606},{"id":"https://openalex.org/C2778559731","wikidata":"https://www.wikidata.org/wiki/Q23808793","display_name":"Radiomics","level":2,"score":0.34769999980926514},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.3452000021934509},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.2946000099182129},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.29429998993873596},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.2928999960422516},{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.2922999858856201},{"id":"https://openalex.org/C534262118","wikidata":"https://www.wikidata.org/wiki/Q177719","display_name":"Medical diagnosis","level":2,"score":0.2858999967575073},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.2856999933719635},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2840000092983246},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.28299999237060547},{"id":"https://openalex.org/C127808970","wikidata":"https://www.wikidata.org/wiki/Q385989","display_name":"Bonferroni correction","level":2,"score":0.2653999924659729},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.26489999890327454},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.263700008392334},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.2590000033378601},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.2531999945640564}],"mesh":[{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000086382","descriptor_name":"COVID-19","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":true},{"descriptor_ui":"D000086382","descriptor_name":"COVID-19","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":true},{"descriptor_ui":"D000086382","descriptor_name":"COVID-19","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":true},{"descriptor_ui":"D000086382","descriptor_name":"COVID-19","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":true},{"descriptor_ui":"D000086402","descriptor_name":"SARS-CoV-2","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000086402","descriptor_name":"SARS-CoV-2","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000086402","descriptor_name":"SARS-CoV-2","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000086402","descriptor_name":"SARS-CoV-2","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000093743","descriptor_name":"Random Forest","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000093743","descriptor_name":"Random Forest","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000093743","descriptor_name":"Random Forest","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000093743","descriptor_name":"Random Forest","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000097188","descriptor_name":"Radiomics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000097188","descriptor_name":"Radiomics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000097188","descriptor_name":"Radiomics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000097188","descriptor_name":"Radiomics","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"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":"D000098415","descriptor_name":"Convolutional Neural Networks","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001185","descriptor_name":"Artificial Intelligence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001185","descriptor_name":"Artificial Intelligence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001185","descriptor_name":"Artificial Intelligence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001185","descriptor_name":"Artificial Intelligence","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":"D011024","descriptor_name":"Pneumonia, Viral","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":true},{"descriptor_ui":"D011024","descriptor_name":"Pneumonia, Viral","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":true},{"descriptor_ui":"D011024","descriptor_name":"Pneumonia, Viral","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":true},{"descriptor_ui":"D011024","descriptor_name":"Pneumonia, Viral","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":true},{"descriptor_ui":"D011857","descriptor_name":"Radiographic Image Interpretation, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D011857","descriptor_name":"Radiographic Image Interpretation, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D011857","descriptor_name":"Radiographic Image Interpretation, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D011857","descriptor_name":"Radiographic Image Interpretation, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D013902","descriptor_name":"Radiography, Thoracic","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D013902","descriptor_name":"Radiography, Thoracic","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D013902","descriptor_name":"Radiography, Thoracic","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D013902","descriptor_name":"Radiography, Thoracic","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true}],"locations_count":3,"locations":[{"id":"doi:10.1007/s10278-025-01670-9","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10278-025-01670-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10278-025-01670-9.pdf","source":{"id":"https://openalex.org/S62275304","display_name":"Journal of Imaging Informatics in Medicine","issn_l":"0897-1889","issn":["0897-1889","1618-727X","2948-2925","2948-2933"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Imaging Informatics in Medicine","raw_type":"journal-article"},{"id":"pmid:40986191","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40986191","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":"Journal of imaging informatics in medicine","raw_type":"Journal Article"},{"id":"pmh:oai:pubmedcentral.nih.gov:13230419","is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13230419/","pdf_url":null,"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":"J Imaging Inform Med","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1007/s10278-025-01670-9","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10278-025-01670-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10278-025-01670-9.pdf","source":{"id":"https://openalex.org/S62275304","display_name":"Journal of Imaging Informatics in Medicine","issn_l":"0897-1889","issn":["0897-1889","1618-727X","2948-2925","2948-2933"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Imaging Informatics in Medicine","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4414425760.pdf","grobid_xml":"https://content.openalex.org/works/W4414425760.grobid-xml"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W1498436455","https://openalex.org/W1678356000","https://openalex.org/W2028911404","https://openalex.org/W2149706766","https://openalex.org/W2165698076","https://openalex.org/W2174661749","https://openalex.org/W2183341477","https://openalex.org/W2325619789","https://openalex.org/W2767128594","https://openalex.org/W2911964244","https://openalex.org/W2919115771","https://openalex.org/W2932988231","https://openalex.org/W2954996726","https://openalex.org/W3013772641","https://openalex.org/W3087345531","https://openalex.org/W3088020307","https://openalex.org/W3100236889","https://openalex.org/W3109495579","https://openalex.org/W4220993589","https://openalex.org/W4239510810","https://openalex.org/W4285495288","https://openalex.org/W4288048173","https://openalex.org/W4292236554","https://openalex.org/W4292457708","https://openalex.org/W4295079380","https://openalex.org/W4308239178","https://openalex.org/W4312443924","https://openalex.org/W4312600574","https://openalex.org/W4378527399","https://openalex.org/W4402283514"],"related_works":[],"abstract_inverted_index":{"The":[0],"application":[1],"of":[2,18,27,82,128,143,160],"artificial":[3],"intelligence":[4],"(AI)":[5],"in":[6,36,73,199,221,230],"medical":[7],"imaging":[8],"has":[9],"revolutionized":[10],"diagnostic":[11,80,200,232],"practices,":[12],"enabling":[13],"advanced":[14],"analysis":[15],"and":[16,29,44,56,97,112,157,163,208],"interpretation":[17],"radiological":[19],"data.":[20],"This":[21,224],"study":[22,225],"presents":[23],"a":[24,227],"comprehensive":[25],"evaluation":[26],"radiomics-based":[28,65,216],"deep":[30,48,105,183],"learning-based":[31],"approaches":[32],"for":[33,101,148,182,196,238],"disease":[34],"detection":[35],"chest":[37],"radiography,":[38],"focusing":[39],"on":[40,166],"COVID-19,":[41],"lung":[42],"opacity,":[43],"viral":[45],"pneumonia.":[46],"While":[47],"learning":[49,106,184,203],"models,":[50,85],"particularly":[51],"convolutional":[52],"neural":[53],"networks":[54],"(CNNs)":[55],"vision":[57],"transformers":[58],"(ViTs),":[59],"learn":[60],"directly":[61],"from":[62],"image":[63],"data,":[64],"models":[66,107,185,204,217,241],"extract":[67],"handcrafted":[68],"features,":[69],"offering":[70,235],"potential":[71],"advantages":[72,181],"data-limited":[74],"scenarios.":[75],"We":[76],"systematically":[77],"compared":[78,145],"the":[79,140],"performance":[81,180,207],"various":[83],"AI":[84,240],"including":[86],"Decision":[87],"Trees,":[88],"Gradient":[89],"Boosting,":[90],"Random":[91,149],"Forests,":[92],"Support":[93],"Vector":[94],"Machines":[95],"(SVMs),":[96],"Multi-Layer":[98],"Perceptrons":[99],"(MLPs)":[100],"radiomics,":[102],"against":[103],"state-of-the-art":[104],"such":[108],"as":[109],"InceptionV3,":[110],"EfficientNetL,":[111],"ConvNeXtXLarge.":[113],"Performance":[114],"was":[115],"evaluated":[116],"across":[117,186,242],"multiple":[118],"sample":[119,164],"sizes.":[120],"At":[121,135],"24":[122],"samples,":[123,137],"EfficientNetL":[124],"achieved":[125,139],"an":[126],"AUC":[127,142],"0.839,":[129],"outperforming":[130],"SVM":[131],"(AUC":[132],"=":[133],"0.762).":[134],"4000":[136],"InceptionV3":[138],"highest":[141],"0.996,":[144],"to":[146],"0.885":[147],"Forest.":[150],"A":[151],"Scheirer-Ray-Hare":[152],"test":[153],"confirmed":[154],"significant":[155],"main":[156],"interaction":[158],"effects":[159],"model":[161,197],"type":[162],"size":[165],"all":[167],"metrics.":[168],"Post":[169],"hoc":[170],"Mann-Whitney":[171],"U":[172],"tests":[173],"with":[174,211],"Bonferroni":[175],"correction":[176],"further":[177],"revealed":[178],"consistent":[179],"most":[187],"conditions.":[188],"These":[189],"findings":[190],"provide":[191],"statistically":[192],"validated,":[193],"data-driven":[194],"recommendations":[195],"selection":[198],"AI.":[201],"Deep":[202],"demonstrated":[205],"higher":[206],"better":[209],"scalability":[210],"increasing":[212],"data":[213],"availability,":[214],"while":[215],"may":[218],"remain":[219],"useful":[220],"low-data":[222],"contexts.":[223],"addresses":[226],"critical":[228],"gap":[229],"AI-based":[231],"research":[233],"by":[234],"practical":[236],"guidance":[237],"deploying":[239],"diverse":[243],"clinical":[244],"environments.":[245]},"counts_by_year":[{"year":2026,"cited_by_count":7}],"updated_date":"2026-08-18T07:49:30.821534","created_date":"2025-10-10T00:00:00"}
