Machine Learning and Artificial Intelligence: Definitions, Applications, and Future Directions

Author:

Helm J. Matthew,Swiergosz Andrew M.,Haeberle Heather S.,Karnuta Jaret M.,Schaffer Jonathan L.,Krebs Viktor E.,Spitzer Andrew I.,Ramkumar Prem N.

Publisher

Springer Science and Business Media LLC

Subject

Orthopedics and Sports Medicine

Reference26 articles.

1. • Bini SA. Artificial intelligence, machine learning, deep learning, and cognitive computing: what do these terms mean and how will they impact health care? J Arthroplast. 2018;33(8):2358–61. https://doi.org/10.1016/j.arth.2018.02.067The purpose of this article was to discuss the fundamentals of artificial intelligence so that practicing surgeons may better understand how and where to apply it. The article touches on the origins of artificial intelligence and its progression into machine learning, as well as the development of artificial neural networks and deep learning algorithms. It provides a foundation for knowledge of machine learning and its use in healthcare.

2. Maxmen JS. The post-physician era : medicine in the twenty-first century. Hoboken: Wiley; 1976.

3. Naylor CD. On the prospects for a (deep) learning health care system. JAMA. 2018;320(11):1099–100. https://doi.org/10.1001/jama.2018.11103.

4. Topol EJ. High-performance medicine: the convergence of human and artificial intelligence. Nat Med. https://doi.org/10.1038/s41591-018-0300-7.

5. •• Haeberle HS, Helm JM, Navarro SM, et al. Artificial intelligence and machine learning in lower extremity arthroplasty: a review. J Arthroplast. 2019. https://doi.org/10.1016/j.arth.2019.05.055The purpose of this review was to (1) summarize and review the most recent applications of artificial intelligence and machine learning–specific to lower extremity arthroplasty, (2) discuss the origins and model-specifics of machine learning, and (3) examine the progression of machine learning into healthcare. This review specifically examines osteoarthritis gait models, joint-specific imaging, and value-based payment models. It is one of the few reviews to look at the advancement and application of machine learning within the field of orthopaedics.

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