Automated arrhythmia detection from electrocardiogram (ECG) signals is crucial and important for the early treatment of cardiac disease (CD). In this investigation, eight machine-learning models have been developed to identify improved ECG arrhythmia...
Brain tumors are the most prevalent and life-threatening cancer; an early and accurate diagnosis of brain tumors increases the chances of patient survival and treatment planning. However, manual tumor detection is a complex, cumbersome and time-consu...
Proceedings of the National Academy of Sciences of the United States of America
Dec 12, 2025
Brain-inspired spiking neural networks (SNNs) have garnered significant research attention in algorithm design and perception applications. However, their potential in the decision-making domain, particularly in model-based reinforcement learning, re...
BACKGROUND: This study aimed to evaluate the efficacy of a convolutional neural network (CNN) model in estimating fetal brain age from MRI scans during second and third trimesters.
Human activity recognition (HAR) has numerous applications due to its widespread use of procurement tools, such as smartphones and video cameras, and its ability to capture data on human activity. HAR became a hot scientific area in the computer visi...
Vision is a fundamental sense that profoundly impacts daily life and independence. For visually impaired people (VIP), the absence or impairment of this sense presents significant challenges, particularly in navigating their environment and identifyi...
Recurrent neural networks (RNNs) have emerged as a prominent tool for modeling cortical function. However, their conventional architecture is fundamentally lacking in physiological and anatomical fidelity, often raising questions regarding the validi...
Biomechanics and modeling in mechanobiology
Dec 12, 2025
Large-scale axonal dynamic simulation is critical to study white matter injury but is prohibitive in computational cost. We solve this challenge by training a convolutional neural network (CNN) that takes fiber strain profiles as inputs to instantly ...
Brain-computer interface (BCI) technology enables direct communication between the human brain and external devices by decoding electroencephalography (EEG)signals into actionable commands. As a noninvasive and portable modality, EEG-based BCIs hold ...
The construction industry has emerged as a major contributor to global energy consumption and greenhouse gas emissions amidst continuously rising worldwide energy demands. Enhancing building energy efficiency represents a critical intervention for ac...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.