Pain assessment in clinical practice largely relies on patient-reported subjectivity. Although previous studies using fMRI and EEG have attempted objective pain evaluation, their focus has been limited to resting conditions. This study aimed to class...
This work introduces a hybrid computational approach in which degree-based topological descriptors are harnessed with the aid of advanced regression models and artificial neural networks (ANNs) to predict the crucial physicochemical properties of 17 ...
BACKGROUND: Biological systems derive from complex interactions between entities ranging from biomolecules to macroscopic structures, forming intricate networks essential for understanding disease mechanisms and developing therapeutic interventions. ...
Pholiota adiposa is recognized for its health benefits, particularly in Alzheimer's disease (AD), but its molecular mechanism remains elusive. Our study employs network pharmacology and machine learning to uncover its therapeutic potential. We constr...
Childhood stunting is a persistent public health challenge in Ethiopia, significantly impacting children's physical growth, cognitive development, and overall well-being. This study overcame a key limitation in previous stunting prediction models by ...
As a typical pest affecting corn yield and safety, corn borer causes serious economic losses worldwide. Climate warming has intensified the occurrence of pest outbreaks in recent years, but the associated risk has not been precisely assessed or under...
Detection of Cardiovascular Diseases (CVDs) has become crucial nowadays, as the World Health Organization (WHO) declares CVDs as the major leading causes of death in the globe. Moreover, the death rate due to CVDs is expected to rise in the next few ...
Parkinson's disease (PD) is a progressive neurological disorder that impairs movement control, leading to symptoms such as tremors, stiffness, and bradykinesia. Early and accurate PD detection is essential for effective management and improving patie...
Universal differential equations (UDEs) are an emerging approach in biomedical systems biology, integrating physiology-driven mathematical models with machine learning for data-driven model discovery in areas where knowledge of the underlying physiol...
Atrial fibrillation (AF) increases the risk of adverse cardiovascular events, yet the underlying biological mechanisms remain unclear. We evaluate a panel of 12 circulating biomarkers representing diverse pathophysiological pathways in 3817 AF patien...
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