Osteoporosis is a prevalent metabolic bone disease that frequently remains undiagnosed due to limited access to bone mineral density (BMD) tests, such as Dual-energy X-ray absorptiometry (DXA). To address this issue, recent research explores alternat...
Gallbladder cancer, a common yet often under diagnosed malignancy, is typically characterized by late detection and a poor prognosis. The rise of deep learning has introduced new methods for its early identification through B-ultrasound imaging, but ...
The primary fatty acid makeup of a comprehensive set of edible oils was ascertained using an electrochemical impedance spectroscopic approach. The electrical signatures of edible oils (i.e impedance spectra) were recorded and a neural network was use...
Journal of chemical information and modeling
Sep 7, 2025
Molecular property prediction has become essential in accelerating advancements in drug discovery and materials science. Graph Neural Networks have recently demonstrated remarkable success in molecular representation learning; however, their broader ...
Domain Generalization (DG) seeks to transfer knowledge from multiple source domains to unseen target domains, even in the presence of domain shifts. Achieving effective generalization typically requires a large and diverse set of labeled source data ...
BMC medical informatics and decision making
Sep 3, 2025
BACKGROUND AND OBJECTIVES: Brain tissue oxygenation is usually inferred from arterial partial pressure of oxygen (paO), which is in turn often inferred from pulse oximetry measurements or other non-invasive proxies. Our aim was to evaluate the feasib...
Melanoma, influenced by changes in deoxyribonucleic acid (DNA), requires early detection for effective treatment. Traditional melanoma research often employs supervised learning methods, which necessitate large, labeled datasets and are sensitive to ...
Self-supervised learning (SSL) has gained significant attention in medical imaging for its ability to leverage large amounts of unlabeled data for effective model pretraining. Among SSL methods, the masked autoencoder (MAE) has proven robust in learn...
The accurate classification of obesity is essential for public health and clinical decision-making. Traditional anthropometric measures such as body mass index (BMI) have limitations in differentiating between fat and lean mass. This study aimed to e...
Understanding how individual differences influence vulnerability to disease and responses to pharmacological treatments represents one of the main challenges in behavioral neuroscience. Nevertheless, inter-individual variability and sex-specific patt...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.