Facial plastic surgery & aesthetic medicine
Apr 12, 2023
Advances in machine learning age progression technology offer the unique opportunity to better understand the public's perception on the aging face. To compare how observers perceive attractiveness and traditional gender traits in faces created wit...
Hepatobiliary & pancreatic diseases international : HBPD INT
Apr 11, 2023
BACKGROUND: Gallbladder carcinoma (GBC) is highly malignant, and its early diagnosis remains difficult. This study aimed to develop a deep learning model based on contrast-enhanced computed tomography (CT) images to assist radiologists in identifying...
BACKGROUND: Stereoelectroencephalography (SEEG) is a critical tool used in the identification of epileptogenic zones. Although stereotactic frame-based SEEG procedures have been performed traditionally, newer robotic-assisted SEEG procedures have bec...
A 61-year-old male presented via referral for mitral regurgitation and was deemed an appropriate robotic surgery candidate for complex mitral valve repair with the maze procedure and patent foramen ovale and left atrial appendage closures, using all ...
Journal of magnetic resonance imaging : JMRI
Apr 6, 2023
BACKGROUND: Deep learning methods have been shown to be useful for segmentation of lower limb muscle MRIs of healthy subjects but, have not been sufficiently evaluated on neuromuscular disease (NDM) patients.
AJR. American journal of roentgenology
Apr 5, 2023
In patients with acute pulmonary embolism (PE), timely intervention (e.g., initiation of anticoagulation) is critical for optimizing clinical outcomes. The purpose of this study was to evaluate the effect of artificial intelligence (AI)-based radio...
PURPOSE: Artificial intelligence-based tools can be leveraged to improve detection and segmentation of brain metastases for stereotactic radiosurgery (SRS). VBrain by Vysioneer Inc. is a deep learning algorithm with recent FDA clearance to assist in ...
Journal of cancer survivorship : research and practice
Apr 3, 2023
PURPOSE: Irradiation of the brain regions from nasopharyngeal carcinoma (NPC) radiotherapy (RT) is frequently unavoidable, which may result in radiation-induced cognitive deficit. Using deep learning (DL), the study aims to develop prediction models ...
PURPOSE: The purpose of this study was to develop and evaluate a deep learning model to detect bone marrow edema (BME) in sacroiliac joints and predict the MRI Assessment of SpondyloArthritis International Society (ASAS) definition of active sacroili...
BACKGROUND: Machine learning (ML) models for early identification of patients at risk of hospital-acquired urinary tract infection (HA-UTI) may enable timely and targeted preventive and therapeutic strategies. However, clinicians are often challenged...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.