A Surgeon’s Guide to Artificial Intelligence-Driven Predictive Models

Abbas M. Hassan, Aashish Rajesh, Malke Asaad, Jonas A. Nelson, J. Henk Coert, Babak J. Mehrara, Charles E. Butler

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)11-19
Number of pages9
JournalAmerican Surgeon
Issue number1
StatePublished - Jan 2023


  • artificial intelligence
  • deep learning
  • machine learning
  • prediction
  • predictive model
  • risk assessment
  • surgery
  • surgery

ASJC Scopus subject areas

  • Surgery


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