BACKGROUND: Accurate mortality risk prediction is crucial for effective cardiovascular risk management. Recent advancements in artificial intelligence (AI) have demonstrated potential in this specific medical field. Qwen-2 and Llama-3 are high-perfor...
Journal of chemical information and modeling
May 12, 2025
Drug-drug interaction (DDI) can compromise therapeutic efficacy and cause detrimental effects in polypharmacy. Computational prediction of DDI has emerged as an alternative approach to time-consuming clinical experiments for investigating potential d...
Journal of chemical information and modeling
May 12, 2025
Machine learning interatomic potentials (MLIPs) have emerged as powerful tools for investigating atomistic systems with high accuracy and a relatively low computational cost. However, a common and unaddressed challenge with many current neural networ...
Journal of chemical information and modeling
May 12, 2025
This study introduces PROFIS, a new generative model capable of the design of structurally novel and target-focused compound libraries. The model relies on a recurrent neural network that was trained to decode embedded molecular fingerprints into SMI...
Journal of chemical information and modeling
May 12, 2025
In chemical reaction network theory, ordinary differential equations are used to model the temporal change of chemical species concentration. As the functional form of these ordinary differential equation systems is derived from an empirical model of...
Journal of chemical information and modeling
May 12, 2025
Neuropeptides are key signaling molecules that regulate fundamental physiological processes ranging from metabolism to cognitive function. However, accurate identification is a huge challenge due to sequence heterogeneity, obscured functional motifs ...
Modern clinical trials can capture tens of thousands of clinicogenomic measurements per individual. Discovering predictive biomarkers, as opposed to prognostic markers, remains challenging. To address this, we present a neural network framework based...
The Purpose of this study is to propose a new integrative framework for athletic performance prediction based on state-of-the-art machine learning analysis and biometric data biometric scanning. By merging physiological signals i.e., Heart rate varia...
Across domains such as visual processing, computer graphics, neuroscience, and biological sciences, geons are recognized as fundamental components of complex shapes. Their theoretical significance has been extensively acknowledged in scientific resea...
Hypoxic-Ischemic Encephalopathy (HIE) occurs in patients who experience a decreased flow of blood and oxygen to the brain, with the optimal window for effective treatment being within the first six hours of life. This puts a significant demand on med...
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