OBJECTIVES: Precisely diagnosing skeletal class is mandatory for correct orthodontic treatment. Artificial intelligence (AI) could increase efficiency during diagnostics and contribute to automated workflows. So far, no AI-driven process can differen...
Biomedical physics & engineering express
Aug 5, 2025
Pulmonary diseases have become one of the main reasons for people's health decline, impacting millions of people worldwide. Rapid advancement of deep learning has significantly impacted medical image analysis by improving diagnostic accuracy and effi...
PURPOSE: To adopt different deep learning (DL) techniques for Essential tremor (ET) and Parkinson's tremor (PST) classification, a collaborative approach to address the misdiagnosis of healthy and PSD patients based on ET and PST's frequency patterns...
Proceedings of the National Academy of Sciences of the United States of America
Aug 4, 2025
Obtaining predictive models of a neural system is notoriously challenging. Detailed models suffer from excess model complexity and are difficult to fit efficiently. Simplified models must negotiate a tradeoff between tractability, predictive power, a...
BACKGROUND: Sphingolipid metabolism (SM) is linked to acute myocardial infarction (AMI), but its role remains unclear. This study explored SM-related genes (SMRGs) in AMI to support clinical diagnosis.
Falling poses a significant health risk to the elderly, often resulting in severe injuries if not promptly addressed. As the global population increases, the frequency of falls increases along with the associated financial burden. Hence, early detect...
Accurately segmenting the pancreas from abdominal computed tomography (CT) images is crucial for detecting and managing pancreatic diseases, such as diabetes and tumors. Type 2 diabetes and metabolic syndrome are associated with pancreatic fat accumu...
BACKGROUND: Proton therapy is commonly used for treating hepatocellular carcinoma (HCC); however, its feasibility can be challenging to assess in large tumors or those adjacent to critical organs at risk (OARs), which are typically assessed only afte...
Spiking neural networks (SNNs) are biologically more plausible and computationally more powerful than artificial neural networks due to their intrinsic temporal dynamics. However, vanilla spiking neurons struggle to simultaneously encode spatiotempor...
This study presents an Internet of Things (IoT)-enabled Deep Learning Monitoring (IoT-E-DLM) model for real-time Athletic Performance (AP) tracking and feedback in collegiate sports. The proposed work integrates advanced wearable sensor technologies ...
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