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Artificial Intelligence and Healthcare Decision-Making

  • Seikai Toyooka
  • , Andreas Persson
  • , R. Kyle Martin
  • , Ayoosh Pareek
  • , Lars Engebretsen

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Artificial intelligence, and more specifically, its subset machine learning, have been increasingly impacting the field of orthopedic surgery. The number of machine learning-related publications within the orthopedic literature has been increasing every year. Models can primarily be used to help clinicians with both diagnostic and prognostic tasks and will likely play a major role in clinical practice in the near future. Despite the many obstacles to overcome in order to achieve the ultimate goal of improved patient care through AI-powered advancements, the future is promising and clinicians should familiarize themselves with the basics of clinical artificial intelligence. Unfortunately, at this time, there has been little widespread adoption of machine learning algorithms into daily practice and many orthopedic surgeons remain cautious regarding these novel statistical techniques. The purpose of this chapter is to introduce artificial intelligence as it relates to orthopedic surgery and sports medicine, providing examples from the literature along the way.

Original languageEnglish (US)
Title of host publicationSports Injuries
Subtitle of host publicationPrevention, Diagnosis, Treatment and Rehabilitation
PublisherSpringer Science+Business Media
Pages293-304
Number of pages12
ISBN (Electronic)9783031583513
ISBN (Print)9783031583506
DOIs
StatePublished - Jan 1 2025

Bibliographical note

Publisher Copyright:
© 2025 Springer Nature Switzerland AG.

Keywords

  • Artificial intelligence
  • Deep learning
  • Machine learning

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