Ruling out rotator cuff tear in shoulder radiograph series using deep learning: redefining the role of conventional radiograph.
Youngjune KimDongjun ChoiKyong Joon LeeYusuhn KangJoong Mo AhnEugene LeeJoon Woo LeeHeung Sik KangPublished in: European radiology (2020)
• The deep learning algorithm can rule out significant rotator cuff tear with a negative likelihood ratio of 0.06 and a negative predictive value of 96.6%. • The deep learning algorithm can guide patients with significant rotator cuff tear to additional shoulder ultrasound or MRI with a sensitivity of 97.3%. • The deep learning algorithm could rule out significant rotator cuff tear in about 30% of patients with clinically suspected rotator cuff tear.