BACKGROUND: The role of reverse total shoulder arthroplasty (rTSA) for glenohumeral osteoarthritis (GHOA) with an intact rotator cuff remains unclear with prior investigations demonstrating similar patient-reported outcome measures (PROMs) to anatomi...
BACKGROUND: Joint arthroplasty registries usually lack information on medical imaging owing to the laborious process of observing and recording, as well as the lack of standard methods to transfer the imaging information to the registries, which can ...
The aim of the present study was to individuate and compare specific machine learning algorithms that could predict postoperative anterior elevation score after reverse shoulder arthroplasty surgery at different time points. Data from 105 patients wh...
BACKGROUND: Technological advancements in implant design and surgical technique have focused on diminishing complications and optimizing performance of reverse shoulder arthroplasty (rTSA). Despite this, there remains a paucity of literature correlat...
BACKGROUND: Reduced bone density is recognized as a predictor for potential complications in reverse shoulder arthroplasty (RSA). While humeral and glenoid planning based on preoperative computed tomography (CT) scans assist in implant selection and ...
Journal of the American Academy of Orthopaedic Surgeons. Global research & reviews
39106479
BACKGROUND: Accurate and precise templating is paramount for anatomic total shoulder arthroplasty (TSA) and reverse total shoulder arthroplasty (RSA) to enhance preoperative planning, streamline surgery, and improve implant positioning. We aimed to e...
Studies in health technology and informatics
39320198
Reoperation is the most significant complication following any surgical procedure. Developing machine learning methods that predict the need for reoperation will allow for improved shared surgical decision making and patient-specific and preoperative...
PURPOSE: Computer vision and artificial intelligence (AI) offer the opportunity to rapidly and accurately interpret standardized x-rays. We trained and validated a machine learning tool that identified key reference points and determined glenoid retr...
PURPOSE: Accurate identification of radiographic landmarks is fundamental to characterizing glenohumeral relationships before and sequentially after shoulder arthroplasty, but manual annotation of these radiographs is laborious. We report on the use ...
BACKGROUND: Increasingly, patients are turning to artificial intelligence (AI) programs such as ChatGPT to answer medical questions either before or after consulting a physician. Although ChatGPT's popularity implies its potential in improving patien...