Artificial Intelligence in Orthopedic Radiography Analysis: A Narrative Review

Overview

Journal Diagnostics (Basel)

Specialty Radiology

Date 2022 Sep 23

PMID 36140636

Authors

Kenneth Chen

Christoph Stotter

Thomas Klestil

Stefan Nehrer

Affiliations

Soon will be listed here.

Abstract

Artificial intelligence (AI) in medicine is a rapidly growing field. In orthopedics, the clinical implementations of AI have not yet reached their full potential. Deep learning algorithms have shown promising results in computed radiographs for fracture detection, classification of OA, bone age, as well as automated measurements of the lower extremities. Studies investigating the performance of AI compared to trained human readers often show equal or better results, although human validation is indispensable at the current standards. The objective of this narrative review is to give an overview of AI in medicine and summarize the current applications of AI in orthopedic radiography imaging. Due to the different AI software and study design, it is difficult to find a clear structure in this field. To produce more homogeneous studies, open-source access to AI software codes and a consensus on study design should be aimed for.

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