A Surgeon's Guide to Artificial Intelligence-Driven Predictive Models.

Journal: The American surgeon
Published Date:

Abstract

Artificial intelligence (AI) focuses on processing and interpreting complex information as well as identifying relationships and patterns among complex data. Artificial intelligence- and machine learning (ML)-driven predictions have shown promising potential in influencing real-time decisions and improving surgical outcomes by facilitating screening, diagnosis, risk assessment, preoperative planning, and shared decision-making. Fundamental understanding of the algorithms, as well as their development and interpretation, is essential for the evolution of AI in surgery. In this article, we provide surgeons with a fundamental understanding of AI-driven predictive models through an overview of common ML and deep learning algorithms, model development, performance metrics and interpretation. This would serve as a basis for understanding ML-based research, while fostering new ideas and innovations for furthering the reach of this emerging discipline.

Authors

  • Abbas M Hassan
    Department of Plastic & Reconstructive Surgery, 571198The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
  • Aashish Rajesh
    Department of Surgery, University of Texas Health Science Center, San Antonio, TX, USA.
  • Malke Asaad
    From the Division of Plastic Surgery, Department of Surgery, Mayo Clinic; the Division of Plastic Surgery, Department of Surgery, Sidra Medicine; and the Department of Surgery, Weill-Cornell Medical College-Qatar.
  • Jonas A Nelson
    Department of Plastic & Reconstructive Surgery, 5803Memorial Sloan Kettering Cancer Center, New York, NY.
  • J Henk Coert
    Department of Plastic and Reconstructive Surgery, 8124University Medical Center Utrecht, Utrecht, Netherlands.
  • Babak J Mehrara
    Department of Plastic & Reconstructive Surgery, 5803Memorial Sloan Kettering Cancer Center, New York, NY.
  • Charles E Butler
    Department of Plastic & Reconstructive Surgery, the University of Texas MD Anderson Cancer Center, Houston, TX, USA.