Segond Fractures Can Be Identified With Excellent Accuracy Utilizing Deep Learning on Anteroposterior Knee Radiographs.
Jacob F OedingAyoosh PareekKyle N KunzeBenedict U NwachukwuHarry G GreditzerChristopher L CampBryan T KellyAndrew D PearleAnil S RanawatRiley J Williamsnull nullPublished in: Arthroscopy, sports medicine, and rehabilitation (2024)
Deep learning can be used for automated Segond fracture identification on radiographs, leading to improved diagnosis of easily missed concomitant injuries, including lateral meniscus tears. Automated identification of Segond fractures can also enable large-scale studies on the incidence and clinical significance of these fractures, which may lead to improved management and outcomes for patients with knee injuries.
Keyphrases
- deep learning
- total knee arthroplasty
- artificial intelligence
- convolutional neural network
- machine learning
- anterior cruciate ligament
- anterior cruciate ligament reconstruction
- knee osteoarthritis
- risk factors
- bioinformatics analysis
- minimally invasive
- metabolic syndrome
- rotator cuff
- adipose tissue
- glycemic control