Gesture recognition based on surface electromyography (sEMG) plays a crucial role in human-computer interaction. By analyzing sEMG signals generated from residual forearm muscle activity in trans-radial amputees, it is possible to predict their hand ...
BACKGROUND: Cardiovascular disease (CVD) is the leading cause of mortality and morbidity in China and worldwide while we are lacking in validated primary prevention model specifically for Chinese. To identify CVD high-risk individuals for early inter...
In the intensive care unit (ICU), managing traumatic brain injury (TBI) patients presents significant challenges due to the dynamic interaction between physiological and clinical markers. This study aims to uncover these subtle interconnections and i...
Predicting the original mass of a retouched scraper has long been a major goal in lithic analysis. It is commonly linked to lithic technological organization of past societies along with notions of stone tool general morphology, standardization throu...
Polycyclic aromatic hydrocarbons (PAHs) generated during lamb roasting pose health risks but are difficult to predict due to their low concentrations and complex features. Existing models fail to address data scarcity and low-concentration prediction...
The excessive use of tetracyclines (TCs) poses a significant threat to human health, necessitating the development of convenient, rapid, and intelligent detection methods for monitoring TCs residues in food products. In this work, we present a hetero...
Site-specific arsenic (As) bioaccessibility data can improve the accuracy of health risk assessments, but direct measurements are costly and time-consuming. Even when available, measured values such as the mean still yield remediation targets below n...
Ecotoxicology and environmental safety
Jul 26, 2025
Environmental pollution plays a major role in the development of prostate cancer (PCA). However, there has been no research on machine learning (ML) modelling between multiple heavy metal exposures and PCA risk. Based on the 8022 samples from the 200...
Journal of chemical information and modeling
Jul 26, 2025
Accurate prediction of molecular properties is crucial for accelerating the development of new drugs, and quantum machine learning (QML) holds great promise in this domain. A typical QML pipeline comprises two core stages: encoding classical data int...
Journal of chemical information and modeling
Jul 26, 2025
Activity cliffs (ACs) are defined as significant changes in biological activity triggered by minor chemical structural modifications. Accurately predicting ACs is crucial for drug discovery and molecular optimization. Existing approaches often overlo...
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