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Challenges of using artificial intelligence to detect valvular heart disease from chest radiography - Authors' reply.
Ueda, Daiju; Ehara, Shoichi; Yamamoto, Akira; Walston, Shannon L; Shimono, Taro; Miki, Yukio.
Affiliation
  • Ueda D; Department of Diagnostic and Interventional Radiology, Osaka Metropolitan University, Osaka, 545-8585, Japan; Graduate School of Medicine, and Smart Life Science Lab, Center for Health Science Innovation, Osaka Metropolitan University, Osaka, 545-8585, Japan. Electronic address: ai.labo.ocu@gmail.co
  • Ehara S; Department of Intensive Care Medicine, Osaka Metropolitan University, Osaka, 545-8585, Japan.
  • Yamamoto A; Department of Diagnostic and Interventional Radiology, Osaka Metropolitan University, Osaka, 545-8585, Japan.
  • Walston SL; Department of Diagnostic and Interventional Radiology, Osaka Metropolitan University, Osaka, 545-8585, Japan.
  • Shimono T; Department of Diagnostic and Interventional Radiology, Osaka Metropolitan University, Osaka, 545-8585, Japan.
  • Miki Y; Department of Diagnostic and Interventional Radiology, Osaka Metropolitan University, Osaka, 545-8585, Japan.
Lancet Digit Health ; 6(1): e10, 2024 Jan.
Article in En | MEDLINE | ID: mdl-38123250
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Artificial Intelligence / Heart Valve Diseases Limits: Humans Language: En Journal: Lancet Digit Health Year: 2024 Document type: Article Country of publication: Reino Unido
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Artificial Intelligence / Heart Valve Diseases Limits: Humans Language: En Journal: Lancet Digit Health Year: 2024 Document type: Article Country of publication: Reino Unido