Your browser doesn't support javascript.
loading
Machine Learning and Precision Medicine in Emergency Medicine: The Basics.
Lee, Sangil; Lam, Samuel H; Hernandes Rocha, Thiago Augusto; Fleischman, Ross J; Staton, Catherine A; Taylor, Richard; Limkakeng, Alexander T.
Afiliación
  • Lee S; Emergency Medicine, University of Iowa Carver College of Medicine, Iowa City, USA.
  • Lam SH; Emergency Medicine, Sutter Medical Center, Sacramento, USA.
  • Hernandes Rocha TA; Division of Emergency Medicine, Department of Surgery, Duke University School of Medicine, Durham, USA.
  • Fleischman RJ; Emergency Medicine, Harbor-UCLA Medical Center, Los Angeles, USA.
  • Staton CA; Division of Emergency Medicine, Department of Surgery, Duke University School of Medicine, Durham, USA.
  • Taylor R; Department of Emergency Medicine, Yale University, New Haven, USA.
  • Limkakeng AT; Division of Emergency Medicine, Department of Surgery, Duke University School of Medicine, Durham, USA.
Cureus ; 13(9): e17636, 2021 Sep.
Article en En | MEDLINE | ID: mdl-34646684
As machine learning (ML) and precision medicine become more readily available and used in practice, emergency physicians must understand the potential advantages and limitations of the technology. This narrative review focuses on the key components of machine learning, artificial intelligence, and precision medicine in emergency medicine (EM). Based on the content expertise, we identified articles from EM literature. The authors provided a narrative summary of each piece of literature. Next, the authors provided an introduction of the concepts of ML, artificial intelligence as an extension of ML, and precision medicine. This was followed by concrete examples of their applications in practice and research. Subsequently, we shared our thoughts on how to consume the existing research in these subjects and conduct high-quality research for academic emergency medicine. We foresee that the EM community will continue to adapt machine learning, artificial intelligence, and precision medicine in research and practice. We described several key components using our expertise.
Palabras clave

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Cureus Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Cureus Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos