INTRODUCTION: ChatGPT, a widely accessible AI program, has demonstrated potential in various healthcare applications, including emergency department (ED) triage, differential diagnosis, and patient education. However, its potential in providing recom...
PURPOSE: Missed fractures are the most common radiologic error in clinical practice, and erroneous classification could lead to inappropriate treatment and unfavorable prognosis. Here, we developed a fully automated deep learning model to detect and ...
OBJECTIVE: This study aimed to use machine learning (ML) to establish risk factor and prediction models of osteonecrosis of the femoral head (ONFH) in patients with femoral neck fractures (FNFs) after internal fixation.
BACKGROUND: Given the huge impact of trauma on hospital systems around the world, several attempts have been made to develop predictive models for the outcomes of trauma victims. The most used, and in many studies most accurate predictive model, is t...
OBJECTIVE: Currently, minimally invasive internal fixation is recommended for the surgical treatment of unstable pelvic fractures. The premise and difficulty of minimally invasive internal fixation are minimally invasive reduction of fractures. This ...
INTRODUCTION: In recent years, the scientific community focused on developing Computer-Aided Diagnosis (CAD) tools that could improve clinicians' bone fractures diagnosis, primarily based on Convolutional Neural Networks (CNNs). However, the discerni...
PURPOSE: Subchondral insufficiency fractures (SIF) and advanced osteoarthritis (OA) of the knee are usually seen in conjunction with bone marrow lesions (BMLs) and their differentiation may pose a significant diagnostic challenge. We aimed to develop...
Artificial intelligence (AI) is a broad term referring to the application of computational algorithms that can analyze large data sets to classify, predict, or gain useful conclusions. Under the umbrella of AI is machine learning (ML). ML is the proc...