Gene-level rare variant association tests (RVATs) are essential for uncovering disease mechanisms and identifying therapeutic targets. Advances in sequence-based machine learning have generated diverse variant pathogenicity scores, creating opportuni...
Driving style heterogeneity significantly influences traffic safety and efficiency in highway weaving areas, yet how operational parameters systematically shape population-level behavioral patterns remains unclear. This study examines the relationshi...
The Sherrington-Kirkpatrick (SK) spin-glass model exhibits well-studied phase transitions that are mostly established using replica-based methods. Regardless of the method used for detection, the intrinsic phase of a system exists whether or not repl...
Novel multifunctional packaging for monitoring and maintaining food freshness has been developed. Bilayer films based on polysaccharides incorporating red cabbage anthocyanins were prepared. Anthocyanins were encapsulated in the inner layer based on ...
The intelligent authentication of whole wheat products remains a significant challenge due to the difficulty in simultaneously monitoring multiple alkylresorcinol (AR) homologues within complex food matrices. To address this, we have developed a nove...
Myocardial ischemia is a major global contributor to mortality. While reperfusion therapy remains the most effective treatment, it paradoxically leads to myocardial ischemia-reperfusion (MI/R) injury, resulting in irreversible cardiac damage for whic...
This study aimed to utilize various machine learning algorithms to develop a predictive model for the progression of severe community-acquired pneumonia (SCAP) in children to critical severe community-acquired pneumonia (cSCAP). Retrospective analysi...
BACKGROUND: Detection of axillary lymph node (LN) involvement is essential for staging breast cancer and optimizing treatment. This proof-of-concept two-center study explored the feasibility of magnetic resonance imaging (MRI) radiomics-based machine...
Selecting molecular panels that are applicable to classify the health state of patients is a common task in omics data analysis. Existing software for molecule selection lacks features to select molecule panels from large data sets, requires programm...
The journal of physical chemistry letters
Nov 30, 2025
This study centers on corrole, an emerging photosensitizer with great application potential, and innovatively develops an intelligent machine learning-based screening strategy. Through integrating molecular descriptor generation, feature engineering,...
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