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Deep Learning of Coronary Calcium Scores From PET/CT Attenuation Maps Accurately Predicts Adverse Cardiovascular Events.
Pieszko, Konrad; Shanbhag, Aakash; Killekar, Aditya; Miller, Robert J H; Lemley, Mark; Otaki, Yuka; Singh, Ananya; Kwiecinski, Jacek; Gransar, Heidi; Van Kriekinge, Serge D; Kavanagh, Paul B; Miller, Edward J; Bateman, Timothy; Liang, Joanna X; Berman, Daniel S; Dey, Damini; Slomka, Piotr J.
Afiliación
  • Pieszko K; Departments of Medicine (Division of Artificial Intelligence in Medicine), Biomedical Sciences and Imaging, Cedars-Sinai Medical Center, Los Angeles, California, USA; Department of Interventional Cardiology and Cardiac Surgery, University of Zielona Góra, Zielona Góra, Poland.
  • Shanbhag A; Departments of Medicine (Division of Artificial Intelligence in Medicine), Biomedical Sciences and Imaging, Cedars-Sinai Medical Center, Los Angeles, California, USA.
  • Killekar A; Departments of Medicine (Division of Artificial Intelligence in Medicine), Biomedical Sciences and Imaging, Cedars-Sinai Medical Center, Los Angeles, California, USA.
  • Miller RJH; Departments of Medicine (Division of Artificial Intelligence in Medicine), Biomedical Sciences and Imaging, Cedars-Sinai Medical Center, Los Angeles, California, USA; Department of Cardiac Sciences, University of Calgary, Calgary, Alberta, Canada.
  • Lemley M; Departments of Medicine (Division of Artificial Intelligence in Medicine), Biomedical Sciences and Imaging, Cedars-Sinai Medical Center, Los Angeles, California, USA.
  • Otaki Y; Departments of Medicine (Division of Artificial Intelligence in Medicine), Biomedical Sciences and Imaging, Cedars-Sinai Medical Center, Los Angeles, California, USA.
  • Singh A; Departments of Medicine (Division of Artificial Intelligence in Medicine), Biomedical Sciences and Imaging, Cedars-Sinai Medical Center, Los Angeles, California, USA.
  • Kwiecinski J; Departments of Medicine (Division of Artificial Intelligence in Medicine), Biomedical Sciences and Imaging, Cedars-Sinai Medical Center, Los Angeles, California, USA; Department of Interventional Cardiology and Angiology, Institute of Cardiology, Warsaw, Poland.
  • Gransar H; Departments of Medicine (Division of Artificial Intelligence in Medicine), Biomedical Sciences and Imaging, Cedars-Sinai Medical Center, Los Angeles, California, USA.
  • Van Kriekinge SD; Departments of Medicine (Division of Artificial Intelligence in Medicine), Biomedical Sciences and Imaging, Cedars-Sinai Medical Center, Los Angeles, California, USA.
  • Kavanagh PB; Departments of Medicine (Division of Artificial Intelligence in Medicine), Biomedical Sciences and Imaging, Cedars-Sinai Medical Center, Los Angeles, California, USA.
  • Miller EJ; Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut, USA.
  • Bateman T; Cardiovascular Imaging Technologies, Kansas City, Missouri, USA.
  • Liang JX; Departments of Medicine (Division of Artificial Intelligence in Medicine), Biomedical Sciences and Imaging, Cedars-Sinai Medical Center, Los Angeles, California, USA.
  • Berman DS; Departments of Medicine (Division of Artificial Intelligence in Medicine), Biomedical Sciences and Imaging, Cedars-Sinai Medical Center, Los Angeles, California, USA.
  • Dey D; Departments of Medicine (Division of Artificial Intelligence in Medicine), Biomedical Sciences and Imaging, Cedars-Sinai Medical Center, Los Angeles, California, USA.
  • Slomka PJ; Departments of Medicine (Division of Artificial Intelligence in Medicine), Biomedical Sciences and Imaging, Cedars-Sinai Medical Center, Los Angeles, California, USA. Electronic address: piotr.slomka@cshs.org.
JACC Cardiovasc Imaging ; 16(5): 675-687, 2023 05.
Article en En | MEDLINE | ID: mdl-36284402
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Enfermedad de la Arteria Coronaria / Aprendizaje Profundo Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: JACC Cardiovasc Imaging Asunto de la revista: ANGIOLOGIA / CARDIOLOGIA / DIAGNOSTICO POR IMAGEM Año: 2023 Tipo del documento: Article País de afiliación: Polonia Pais de publicación: Estados Unidos
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Enfermedad de la Arteria Coronaria / Aprendizaje Profundo Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: JACC Cardiovasc Imaging Asunto de la revista: ANGIOLOGIA / CARDIOLOGIA / DIAGNOSTICO POR IMAGEM Año: 2023 Tipo del documento: Article País de afiliación: Polonia Pais de publicación: Estados Unidos