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The effect of using a large language model to respond to patient messages.
Chen, Shan; Guevara, Marco; Moningi, Shalini; Hoebers, Frank; Elhalawani, Hesham; Kann, Benjamin H; Chipidza, Fallon E; Leeman, Jonathan; Aerts, Hugo J W L; Miller, Timothy; Savova, Guergana K; Gallifant, Jack; Celi, Leo A; Mak, Raymond H; Lustberg, Maryam; Afshar, Majid; Bitterman, Danielle S.
Afiliación
  • Chen S; Artificial Intelligence in Medicine Program, Mass General Brigham, Harvard Medical School, Boston, MA, USA; Department of Radiation Oncology, Brigham and Women's Hospital and Dana-Farber Cancer Institute, Boston, MA 02115, USA; Computational Health Informatics Program, Boston Children's Hospital, Ha
  • Guevara M; Artificial Intelligence in Medicine Program, Mass General Brigham, Harvard Medical School, Boston, MA, USA; Department of Radiation Oncology, Brigham and Women's Hospital and Dana-Farber Cancer Institute, Boston, MA 02115, USA.
  • Moningi S; Department of Radiation Oncology, Brigham and Women's Hospital and Dana-Farber Cancer Institute, Boston, MA 02115, USA.
  • Hoebers F; Artificial Intelligence in Medicine Program, Mass General Brigham, Harvard Medical School, Boston, MA, USA; Department of Radiation Oncology, Brigham and Women's Hospital and Dana-Farber Cancer Institute, Boston, MA 02115, USA; Department of Radiation Oncology, GROW School for Oncology and Reproduct
  • Elhalawani H; Department of Radiation Oncology, Brigham and Women's Hospital and Dana-Farber Cancer Institute, Boston, MA 02115, USA.
  • Kann BH; Artificial Intelligence in Medicine Program, Mass General Brigham, Harvard Medical School, Boston, MA, USA; Department of Radiation Oncology, Brigham and Women's Hospital and Dana-Farber Cancer Institute, Boston, MA 02115, USA.
  • Chipidza FE; Department of Radiation Oncology, Brigham and Women's Hospital and Dana-Farber Cancer Institute, Boston, MA 02115, USA.
  • Leeman J; Department of Radiation Oncology, Brigham and Women's Hospital and Dana-Farber Cancer Institute, Boston, MA 02115, USA.
  • Aerts HJWL; Artificial Intelligence in Medicine Program, Mass General Brigham, Harvard Medical School, Boston, MA, USA; Department of Radiation Oncology, Brigham and Women's Hospital and Dana-Farber Cancer Institute, Boston, MA 02115, USA; Radiology and Nuclear Medicine, GROW and Cardiovascular Research Institu
  • Miller T; Computational Health Informatics Program, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
  • Savova GK; Computational Health Informatics Program, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
  • Gallifant J; Laboratory for Computational Physiology, Massachusetts Institute of Technology, Cambridge, MA, USA.
  • Celi LA; Laboratory for Computational Physiology, Massachusetts Institute of Technology, Cambridge, MA, USA; Division of Pulmonary, Critical Care and Sleep Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA; Department of Biostatistics, Harvard T H Chan School of Public Health, Boston, MA, USA.
  • Mak RH; Artificial Intelligence in Medicine Program, Mass General Brigham, Harvard Medical School, Boston, MA, USA; Department of Radiation Oncology, Brigham and Women's Hospital and Dana-Farber Cancer Institute, Boston, MA 02115, USA.
  • Lustberg M; Department of Medical Oncology, Yale School of Medicine, New Haven, CT, USA.
  • Afshar M; Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.
  • Bitterman DS; Artificial Intelligence in Medicine Program, Mass General Brigham, Harvard Medical School, Boston, MA, USA; Department of Radiation Oncology, Brigham and Women's Hospital and Dana-Farber Cancer Institute, Boston, MA 02115, USA; Computational Health Informatics Program, Boston Children's Hospital, Ha
Lancet Digit Health ; 6(6): e379-e381, 2024 Jun.
Article en En | MEDLINE | ID: mdl-38664108

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Lancet Digit Health Año: 2024 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Lancet Digit Health Año: 2024 Tipo del documento: Article
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