Deep Learning Assistance Closes the Accuracy Gap in Fracture Detection Across Clinician Types.
Journal:
Clinical orthopaedics and related research
Published Date:
Sep 9, 2022
Abstract
BACKGROUND: Missed fractures are the most common diagnostic errors in musculoskeletal imaging and can result in treatment delays and preventable morbidity. Deep learning, a subfield of artificial intelligence, can be used to accurately detect fractures by training algorithms to emulate the judgments of expert clinicians. Deep learning systems that detect fractures are often limited to specific anatomic regions and require regulatory approval to be used in practice. Once these hurdles are overcome, deep learning systems have the potential to improve clinician diagnostic accuracy and patient care.