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.

中文翻译：

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深度学习辅助缩小了不同类型临床医生在骨折检测中的准确性差距。

漏诊骨折是肌肉骨骼成像中最常见的诊断错误，可能导致治疗延误和可预防的发病率。深度学习是人工智能的一个子领域，可以通过训练算法来模拟临床专家的判断，从而准确检测骨折。检测骨折的深度学习系统通常仅限于特定解剖区域，需要监管部门批准才能在实践中使用。一旦克服了这些障碍，深度学习系统就有可能提高临床诊断的准确性和患者护理。