This study addresses the critical need for effective Talent Retention (TR) strategies in the
context of Work 4.0, which is characterized by rapid technological advances and significant …

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that involves gradual
memory loss and eventually leads to severe cognitive decline at the final stage. Advanced …

The random vector functional link (RVFL) network is well-regarded for its strong
generalization capabilities in the field of machine learning. However, its inherent …

The brain is a complex system with multiple scales and hierarchies, making it challenging to
identify abnormalities in individuals with mental disorders. The dynamic segregation and …

The classification performance of the random vector functional link (RVFL), a randomized
neural network, has been widely acknowledged. However, due to its shallow learning …

The analysis of multi-omics biomedical data has become increasingly critical in clinical
decision-making for brain diseases like Alzheimer's Disease (AD). However, the inherent …

In real-world applications, class-imbalanced datasets pose significant challenges for
machine learning algorithms, such as support vector machines (SVMs), particularly in …

Alzheimer's disease (AD) is a condition with a complex pathogenesis, sometimes hereditary,
characterized by the loss of neurons and synapses, along with the presence of senile …

This study constructs quantitative network diagnosis and treatment inference rules for
Traditional Chinese Medicine (TCM) in treating coronary heart disease (CHD) based on …