Literature DB >> 34191083

Deciphering musculoskeletal artificial intelligence for clinical applications: how do I get started?

Simukayi Mutasa1, Paul H Yi2.   

Abstract

Artificial intelligence (AI) represents a broad category of algorithms for which deep learning is currently the most impactful. When electing to begin the process of building an adequate fundamental knowledge base allowing them to decipher machine learning research and algorithms, clinical musculoskeletal radiologists currently have few options to turn to. In this article, we provide an introduction to the vital terminology to understand, how to make sense of data splits and regularization, an introduction to the statistical analyses used in AI research, a primer on what deep learning can or cannot do, and a brief overview of clinical integration methods. Our goal is to improve the readers' understanding of this field.
© 2021. ISS.

Entities:  

Keywords:  Artificial intelligence; Deep learning; Introduction; Machine learning; Musculoskeletal radiology

Mesh:

Year:  2021        PMID: 34191083     DOI: 10.1007/s00256-021-03850-4

Source DB:  PubMed          Journal:  Skeletal Radiol        ISSN: 0364-2348            Impact factor:   2.199


  1 in total

Review 1.  Deep learning guided stroke management: a review of clinical applications.

Authors:  Rui Feng; Marcus Badgeley; J Mocco; Eric K Oermann
Journal:  J Neurointerv Surg       Date:  2017-09-27       Impact factor: 5.836

  1 in total

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