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Effect of Training Data Volume on Performance of Convolutional Neural Network Pneumothorax Classifiers.
Thian, Yee Liang; Ng, Dian Wen; Hallinan, James Thomas Patrick Decourcy; Jagmohan, Pooja; Sia, Soon Yiew; Mohamed, Jalila Sayed Adnan; Quek, Swee Tian; Feng, Mengling.
Affiliation
  • Thian YL; Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Queenstown, 119074, Singapore. yee_liang_thian@nuhs.edu.sg.
  • Ng DW; Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Queenstown, 119074, Singapore.
  • Hallinan JTPD; Saw Swee Hock School of Public Health, School of Computer Science, Yong Loo Lin School of Medicine, National University of Singapore, 12 Science Drive 2, #10-01, Queenstown, 117549, Singapore.
  • Jagmohan P; Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Queenstown, 119074, Singapore.
  • Sia SY; Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Queenstown, 119074, Singapore.
  • Mohamed JSA; Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Queenstown, 119074, Singapore.
  • Quek ST; Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Queenstown, 119074, Singapore.
  • Feng M; Salmaniya Medical Complex Rd 2904, Manama, Bahrain.
J Digit Imaging ; 35(4): 881-892, 2022 08.
Article de En | MEDLINE | ID: mdl-35239091
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Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Pneumothorax / Apprentissage profond Type d'étude: Diagnostic_studies Limites: Humans Langue: En Journal: J Digit Imaging Sujet du journal: DIAGNOSTICO POR IMAGEM / INFORMATICA MEDICA / RADIOLOGIA Année: 2022 Type de document: Article Pays d'affiliation: Singapour Pays de publication: États-Unis d'Amérique
Texte intégral
Ajouter à My VHL
Imprimer
XML
PubMed Links
Recherche sur Google

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Pneumothorax / Apprentissage profond Type d'étude: Diagnostic_studies Limites: Humans Langue: En Journal: J Digit Imaging Sujet du journal: DIAGNOSTICO POR IMAGEM / INFORMATICA MEDICA / RADIOLOGIA Année: 2022 Type de document: Article Pays d'affiliation: Singapour Pays de publication: États-Unis d'Amérique