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A foundation for evaluating the surgical artificial intelligence literature.
Hashimoto, Daniel A; Sambasastry, Sai Koushik; Singh, Vivek; Kurada, Sruthi; Altieri, Maria; Yoshida, Takuto; Madani, Amin; Jogan, Matjaz.
Afiliação
  • Hashimoto DA; Penn Computer Assisted Surgery and Outcomes Laboratory, Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA; Global Surgical AI Collaborative, Toronto, ON,
  • Sambasastry SK; Penn Computer Assisted Surgery and Outcomes Laboratory, Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA.
  • Singh V; Penn Computer Assisted Surgery and Outcomes Laboratory, Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
  • Kurada S; Penn Computer Assisted Surgery and Outcomes Laboratory, Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA.
  • Altieri M; Penn Computer Assisted Surgery and Outcomes Laboratory, Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Global Surgical AI Collaborative, Toronto, ON, USA.
  • Yoshida T; Surgical AI Research Academy, Department of Surgery, University Health Network, Toronto, ON, USA.
  • Madani A; Global Surgical AI Collaborative, Toronto, ON, USA; Surgical AI Research Academy, Department of Surgery, University Health Network, Toronto, ON, USA.
  • Jogan M; Penn Computer Assisted Surgery and Outcomes Laboratory, Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Eur J Surg Oncol ; : 108014, 2024 Feb 10.
Article em En | MEDLINE | ID: mdl-38360498
ABSTRACT
With increasing growth in applications of artificial intelligence (AI) in surgery, it has become essential for surgeons to gain a foundation of knowledge to critically appraise the scientific literature, commercial claims regarding products, and regulatory and legal frameworks that govern the development and use of AI. This guide offers surgeons a framework with which to evaluate manuscripts that incorporate the use of AI. It provides a glossary of common terms, an overview of prerequisite knowledge to maximize understanding of methodology, and recommendations on how to carefully consider each element of a manuscript to assess the quality of the data on which an algorithm was trained, the appropriateness of the methodological approach, the potential for reproducibility of the experiment, and the applicability to surgical practice, including considerations on generalizability and scalability.
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Texto completo: 1 Coleções: 01-internacional Temas: Geral Base de dados: MEDLINE Tipo de estudo: Guideline Idioma: En Revista: Eur J Surg Oncol Assunto da revista: NEOPLASIAS Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Temas: Geral Base de dados: MEDLINE Tipo de estudo: Guideline Idioma: En Revista: Eur J Surg Oncol Assunto da revista: NEOPLASIAS Ano de publicação: 2024 Tipo de documento: Article