Researchers publishing in Computational Biomedicine have developed a novel artificial intelligence framework that improves epileptic seizure prediction by combining bidirectional long short-term memory networks with a channel attention mechanism. The study highlights how interpretable deep learning models may help identify critical preictal EEG patterns and support the development of more reliable seizure prediction systems.Researchers publishing in Computational Biomedicine have developed a novel artificial intelligence framework that improves epileptic seizure prediction by combining bidirectional long short-term memory networks with a channel attention mechanism. The study highlights how interpretable deep learning models may help identify critical preictal EEG patterns and support the development of more reliable seizure prediction systems.

A study finds that “preparing” biochar through composting can make it far more effective for improving soil fertility and boosting plant growth.

A study has captured, in real time and in three dimensions, how a single piece of biomass changes as it is heated into biochar, offering fresh clues for designing more effective carbon materials for water cleanup, soil improvement, catalysis, and climate-related applications.

Researchers publishing in Computational Biomedicine have developed a novel artificial intelligence framework, MIGDTA, that integrates graph neural networks and multi-source biological information to enhance drug–target affinity prediction. The study highlights how combining molecular structure, biological descriptors, and interaction networks could accelerate drug discovery and repositioning.

Researchers publishing in Computational Biomedicine have introduced a novel multi-modal artificial intelligence framework, “MediHerb,” designed to improve disease inference through Traditional Chinese Medicine (TCM) knowledge integration. The study highlights how combining biomedical data, molecular information, and herbal prescription knowledge may advance interpretable AI-driven healthcare models.

A new study outlines a comprehensive framework leveraging AI and big data to combat illegal plant trade, addressing global biodiversity threats with technological innovation.

Numerical simulation is essential for predicting how complex mechanical systems move, from robots and vehicles to deployable aerospace structures.

Single-nucleus RNA-seq atlas of equine skeletal muscle reveals donkey and horse distinct cell types, with species-specific age-related shifts in muscle fiber composition. The conserved upregulation pattern of LDHA reveals the critical role of propanoate metabolism in energy supply for equine locomotion. Cross-species transcriptomic comparison delineates a highly conserved atlas of skeletal muscle cell types.