AI Medical Compendium Journal:
Journal of shoulder and elbow surgery

Showing 1 to 10 of 18 articles

Improving readability of shoulder and elbow surgery online patient education material with Chat GPT (Chat Generative Pretrained Transformer) 4.

Journal of shoulder and elbow surgery
BACKGROUND: Health literacy is crucial for effective doctor-patient communication, particularly for surgical patients who need to comprehend complex procedures and care protocols. The American Medical Association and National Institutes of Health sug...

Assessment and comparison of artificial intelligence-generated information regarding shoulder arthroplasty from multiple interfaces.

Journal of shoulder and elbow surgery
BACKGROUND: This study aims to analyze and compare the quality, accuracy, and readability of information regarding anatomic total shoulder arthroplasty (aTSA) and reverse total shoulder arthroplasty (rTSA) provided by various AI interfaces (Open AI's...

Can ChatGPT reliably answer the most common patient questions regarding total shoulder arthroplasty?

Journal of shoulder and elbow surgery
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...

Machine learning models can define clinically relevant bone density subgroups based on patient-specific calibrated computed tomography scans in patients undergoing reverse shoulder arthroplasty.

Journal of shoulder and elbow surgery
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 ...

The relationship between design-based lateralization, humeral bearing design, polyethylene angle, and patient-related factors on surgical complications after reverse shoulder arthroplasty: a machine learning analysis.

Journal of shoulder and elbow surgery
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...

Artificial intelligence in shoulder and elbow surgery: overview of current and future applications.

Journal of shoulder and elbow surgery
Artificial intelligence (AI) is amongst the most rapidly growing technologies in orthopedic surgery. With the exponential growth in healthcare data, computing power, and complex predictive algorithms, this technology is poised to aid providers in dat...

Automated detection and classification of the rotator cuff tear on plain shoulder radiograph using deep learning.

Journal of shoulder and elbow surgery
BACKGROUND: The diagnosis of rotator cuff tears (RCTs) using radiographs alone is clinically challenging; thus, the utility of deep learning algorithms based on convolutional neural networks has been remarkable in the field of medical imaging recogni...

Deep learning to automatically classify very large sets of preoperative and postoperative shoulder arthroplasty radiographs.

Journal of shoulder and elbow surgery
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 ...

Glenoid segmentation from computed tomography scans based on a 2-stage deep learning model for glenoid bone loss evaluation.

Journal of shoulder and elbow surgery
BACKGROUND: The best-fitting circle drawn by computed tomography (CT) reconstruction of the en face view of the glenoid bone to measure the bone defect is widely used in clinical application. However, there are still some limitations in practical app...