Cell motility in dense cell collectives is pivotal in various diseases like cancer metastasis and asthma. A central aspect in these phenomena is the heterogeneity in cell motility, but identifying the motility of individual cells is challenging. Prev...
AIMS: Our aim is to develop a deep learning-based system for automatically identifying and classifying benign and malignant tumours of the eyelid to improve diagnostic accuracy and efficiency.
Selection of the optimal makeup solvent composition is critical for achieving sensitive and reproducible ionization in supercritical fluid chromatography-mass spectrometry (SFC-MS). This study investigated the ionization processes in a spray-based io...
In magnetic resonance imaging (MRI), variations in scan parameters and scanner specifications can result in differences in image appearance. To minimize these differences, harmonization in MRI has been suggested as a crucial image processing techniqu...
High-speed and accuracy identification of pathogens has become increasingly critical in both individual patient care and public health. Artificial intelligence (AI)-assisted surface-enhanced Raman scattering (SERS) biosensors enable simultaneous iden...
Understanding microplastics' (MPs) ecological impact necessitates their precise identification. To address the issue of the competitive adaptive reweighted sampling (CARS) algorithm extracting numerous feature wavenumber points (FWPs) that often miss...
The absence of effective public databases greatly limits high-throughput prediction of hormonal effects mediated by nuclear receptors in aquatic organisms. In this study, we developed novel strategies for multi-species screening of estrogen receptor ...
Memristors exhibit significant potential for neuromorphic computing due to their unique properties. This study introduces a heterojunction nanofluidic memristor (HJNFM) and explores its applications in simulating synapses and constructing neural netw...
Raman imaging utilizes molecular fingerprint information to visualize the spatial distribution of a substance within the scanned area. Subject to its scanning mechanism, it usually costs a prolonged data acquisition duration for achieving high-resolu...
Journal of chemical information and modeling
Aug 11, 2025
Molecular dynamics (MD) simulations are vital for exploring complex systems in computational physics and chemistry. While machine learning methods dramatically reduce computational costs relative to ab initio methods, their accuracy in long-lasting s...
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