Abstract
Applications of artificial intelligence, specifically machine learning, are becoming increasingly popular in Orthopaedic Surgery, and medicine as a whole. This growing interest is shared by data scientists and physicians alike. However, there is an asymmetry of understanding of the developmental process and potential applications of machine learning. As new technology will undoubtedly affect clinical practice in the coming years, it is important for physicians to understand how these processes work. The purpose of this paper is to provide clarity and a general framework for building and assessing machine learning models.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 3917-3923 |
| Number of pages | 7 |
| Journal | Knee Surgery, Sports Traumatology, Arthroscopy |
| Volume | 30 |
| Issue number | 12 |
| DOIs | |
| State | Published - Dec 2022 |
Bibliographical note
Publisher Copyright:© 2022, The Author(s) under exclusive licence to European Society of Sports Traumatology, Knee Surgery, Arthroscopy (ESSKA).
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