Automatic Deep Learning Assisted Detection and Grading of Abnormalities in Knee MRI Studies

"Just Accepted" papers have undergone full peer review and have been accepted for publication in Radiology: Artificial Intelligence. This article will undergo copyediting, layout, and proof review before it is published in its final version. Please note that during production of the final copyedited article, errors may be discovered which could affect the content. To test the hypothesis that artificial intelligence (AI) techniques can aid in identifying and assessing lesion severity in cartilage, bone marrow, meniscus, and anterior cruciate ligament (ACL) in the knee, improving overall MRI interreader agreement. This retrospective study was conducted on 1435 knee MRIs (n 294 patients, mean age, 43 15 years, 153 women), collected within three previous studies (from 2011 to 2014).