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Automated segmentation by SCA-UNet can be directly used for radiomics diagnosis of thymic epithelial tumors.
European journal of radiology
Feb 20, 2025
BACKGROUND: Automatic segmentation of thymic lesions in preoperative computed tomography (CT) images is crucial for accurate diagnosis but remains time-consuming. Although UNet is widely used in medical imaging, its performance is limited by the inhe...
A multi-task self-supervised approach for mass detection in automated breast ultrasound using double attention recurrent residual U-Net.
Computers in biology and medicine
Feb 20, 2025
Breast cancer is the most common and lethal cancer among women worldwide. Early detection using medical imaging technologies can significantly improve treatment outcomes. Automated breast ultrasound, known as ABUS, offers more advantages compared to ...
Combining machine learning models and rule engines in clinical decision systems: Exploring optimal aggregation methods for vaccine hesitancy prediction.
Computers in biology and medicine
Feb 20, 2025
BACKGROUND: With the increasing application of artificial intelligence (AI) technologies in the healthcare sector and the emergence of new solutions, such as large language models, there is a growing need to combine medical knowledge, often expressed...
Characterizing patients at higher cardiovascular risk for prescribed stimulants: Learning from health records data with predictive analytics and data mining techniques.
Computers in biology and medicine
Feb 20, 2025
OBJECTIVE: Given the significantly increased number of individuals prescribed stimulants in the past decade, there has been growing concern regarding the risk of cardiovascular events among adults on stimulant therapy. We aimed to quantify the added ...
Can AI-generated faces serve as fillers in eyewitness lineups?
Memory (Hove, England)
Feb 20, 2025
To create a photo lineup for an eyewitness, police embed the suspect in a group of similar-looking individuals (i.e., fillers). If the witness selects the suspect from these photos of similar-looking people, then this provides evidence they remember ...
Artificial intelligence versus neurologists: A comparative study on multiple sclerosis expertise.
Clinical neurology and neurosurgery
Feb 20, 2025
INTRODUCTION: Multiple sclerosis (MS) is an autoimmune neurodegenerative disease affecting the central nervous system. MS diagnosis is complex, requiring magnetic resonance imaging and cerebrospinal fluid analysis due to the lack of definitive biomar...
Assessment of breast composition in MRI using artificial intelligence - A systematic review.
Radiography (London, England : 1995)
Feb 20, 2025
INTRODUCTION: Magnetic Resonance Imaging (MRI) performs a critical role in breast cancer diagnosis, especially for high-risk populations e.g. family history. MRI could take advantage of the implementation of artificial intelligence (AI). AI assessmen...
Effect of Parallel Cognitive-Motor Training Tasks on Hemodynamic Responses in Robot-Assisted Rehabilitation.
Brain connectivity
Feb 20, 2025
Previous studies suggest that the combination of robot-assisted training with other concurrent tasks may promote the functional recovery and improvement better than the single task. It is well-established that robot-assisted rehabilitation training ...
Development of a Machine-Learning Algorithm to Identify Cauda Equina Compression on Magnetic Resonance Imaging Scans.
World neurosurgery
Feb 20, 2025
OBJECTIVE: Cauda equina syndrome (CES) poses significant neurological risks if untreated. Diagnosis relies on clinical and radiological features. As the symptoms are often nonspecific and common, the diagnosis is usually made after a magnetic resonan...
Learning-based inference of longitudinal image changes: Applications in embryo development, wound healing, and aging brain.
Proceedings of the National Academy of Sciences of the United States of America
Feb 20, 2025
Longitudinal imaging data are routinely acquired for health studies and patient monitoring. A central goal in longitudinal studies is tracking relevant change over time. Traditional methods remove nuisance variation with custom pipelines to focus on ...
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