Diagnostic and interventional imaging
Sep 19, 2024
PURPOSE: The purpose of this study was to compare the diagnostic performance of an artificial intelligence (AI) solution for the detection of fractures of pelvic, proximal femur or extremity fractures in adults with radiologist interpretation of radi...
OBJECTIVE: To explore the potential of the deep learning reconstruction (DLR) for ultralow dose calcium scoring CT (CSCT) with simultaneously reduced tube voltage and current.
Evaluating Community-Acquired Pneumonia (CAP) is crucial for determining appropriate treatment methods. In this study, we established a machine learning model using radiomics and clinical features to rapidly and accurately identify Severe Community-A...
Journal of orthopaedic surgery and research
Sep 19, 2024
PURPOSE: The implementation of artificial intelligence (AI) in health care is gaining popularity. Many publications describe powerful AI-enabled algorithms. Yet there's only scarce evidence for measurable value in terms of patient outcomes, clinical ...
Pediatric head trauma is a significant cause of morbidity and mortality, with children, particularly those under two years old, being more susceptible to skull fractures due to their unique physiological and developmental characteristics. A recent st...
PURPOSE: Retrospectively compare image quality, radiologist diagnostic confidence, and time for images to reach PACS for contrast enhanced abdominopelvic CT examinations created on the scanner console by technologists versus those generated automatic...
Lung cancer is the most common causes of death among all cancer-related diseases. A lung scan examination of the patient is the primary diagnostic technique. This scan analysis pertains to an MRI, CT, or X-ray. The automated classification of lung ca...
RATIONALE AND OBJECTIVES: Traumatic neuroradiological emergencies necessitate rapid and accurate diagnosis, often relying on computed tomography (CT). However, the associated ionizing radiation poses long-term risks. Modern artificial intelligence re...
Computational modeling of cardiovascular function has become a critical part of diagnosing, treating and understanding cardiovascular disease. Most strategies involve constructing anatomically accurate computer models of cardiovascular structures, wh...