AI Medical Compendium Journal:
Joint diseases and related surgery

Showing 1 to 8 of 8 articles

Assessing the performance of ChatGPT-4o on the Turkish Orthopedics and Traumatology Board Examination.

Joint diseases and related surgery
OBJECTIVES: This study aims to assess the overall performance of ChatGPT version 4-omni (GPT-4o) on the Turkish Orthopedics and Traumatology Board Examination (TOTBE) using actual examinees as a reference point to evaluate and compare the performance...

Automated fracture detection in the ulna and radius using deep learning on upper extremity radiographs.

Joint diseases and related surgery
OBJECTIVES: This study aimed to detect single or multiple fractures in the ulna or radius using deep learning techniques fed on upper-extremity radiographs.

The diagnosis of femoroacetabular impingement can be made on pelvis radiographs using deep learning methods.

Joint diseases and related surgery
OBJECTIVES: The aim of this study was to evaluate diagnostic ability of deep learning models, particularly convolutional neural network models used for image classification, for femoroacetabular impingement (FAI) using hip radiographs.

Diagnosis of osteoarthritic changes, loss of cervical lordosis, and disc space narrowing on cervical radiographs with deep learning methods.

Joint diseases and related surgery
OBJECTIVES: In this study, we aimed to differentiate normal cervical graphs and graphs of diseases that cause mechanical neck pain by using deep convolutional neural networks (DCNN) technology.

A brief history of artificial intelligence and robotic surgery in orthopedics & traumatology and future expectations.

Joint diseases and related surgery
Recently, the rate of the production and renewal of information makes it almost impossible to be updated. It is quite difficult to process and interpret large amounts of data by human beings. Unlimited memory capacities, learning abilities, artificia...