人工智能
计算机科学
口译(哲学)
机器学习
数据科学
程序设计语言
作者
Abbas M. Hassan,Aashish Rajesh,Malke Asaad,Nelson A Jonas,J. Henk Coert,Babak J. Mehrara,Charles E. Butler
标识
DOI:10.1177/00031348221103648
摘要
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.
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