Environmental monitoring and assessment
Jan 3, 2026
Artificial neural networks (ANNs) are widely applied in air quality modelling because they can capture nonlinear interactions among pollutants and support reliable air pollutant index (API) forecasting. This study aims to identify the pollutants that...
Recent advancements in spiking neural networks (SNNs) have drawn inspiration from the human brain's distinctive capabilities, leading to significant impacts on various aspects of our lives and scientific endeavors. The development of hardware-based S...
Journal of chemical information and modeling
Dec 31, 2025
Drug-target affinity (DTA) prediction is crucial in drug discovery. It enables researchers to elucidate the complex interaction mechanisms between candidate drugs and biological targets. However, current methods have limitations in capturing global s...
Journal of chemical information and modeling
Dec 31, 2025
The accurate and efficient computational identification of interferon-gamma-inducing epitopes (IFNgIE) is a critical bottleneck in the design of next-generation vaccines and immunotherapies. Existing computational models, while adept at learning sequ...
This work proposes a stress classification system from the electroencephalogram (EEG) signals collected from the stress subjects. The scheme extracts the phase-controlled Bi-channel adaptive features using a pair of EEG signals. The proposed adaptive...
Journal of chemical information and modeling
Dec 30, 2025
Combination therapy is a method of treating complex diseases by using multiple drugs, which has the advantages of good efficacy and few toxic side effects. It has been widely used in clinical research. The significant increase in the number of drug c...
Skin cancer is the abnormal growth of skin cells, most often developing on skin exposed to the sun. It is among the most fatal forms of cancer, making its early detection and therapy crucial. In addition to conventional techniques, deep learning meth...
BACKGROUND: Artificial intelligence (AI) has demonstrated superior diagnostic accuracy compared with medical practitioners, highlighting its growing importance in health care. SMART-Pred (Shiny Multi-Algorithm R Tool for Predictive Modeling) is an in...
This paper proposes a hybrid ensemble classifier with denoising autoencoder (ECDAE) framework to address reliability and robustness challenges in cooperative spectrum sensing (CSS) for cognitive radio networks (CRNs). The proposed framework first emp...
Accurate Remaining Useful Life (RUL) prediction for Lithium-ion batteries is critical for system safety, yet its efficacy is frequently limited by data scarcity in industrial contexts. The robustness of hybrid architectures combining Convolutional Ne...
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