Machine learning heavily relies on data, but real-world applications often encounter various
data-related issues. These include data of poor quality, insufficient data points leading to …

The importance of uncertainty quantification is increasingly recognized in the diverse field of
machine learning. Accurately assessing model prediction uncertainty can help provide …

Clinical trials are pivotal for developing new medical treatments, yet they typically pose
some risks such as patient mortality, adverse events, and enrollment failure that waste …

This paper presents a systematic literature review on Brain-Computer Interfaces (BCIs) in
the context of Machine Learning. Our focus is on Electroencephalography (EEG) research …

The clinical trial process, a critical phase in drug development, is essential for developing
new treatments. The primary goal of interventional clinical trials is to evaluate the safety and …

Allostery is a fundamental process in regulating protein activities. The discovery, design, and
development of allosteric drugs demand better identification of allosteric sites. Several …

Clinical trials need to recruit a sufficient number of volunteer patients to demonstrate the
statistical power of the treatment (eg, a new drug) in curing a certain disease. Clinical trial …

Motivation Ideally, a molecularly distinct subtype would be composed of molecular features
that are expressed uniquely in the subtype of interest but in no others—so-called marker …

Bringing a novel drug from the original idea to market typically requires more than ten years
and billions of dollars. To alleviate the heavy burden, a natural idea is to reuse the approved …

Background: Clinical trial is a crucial step in the development of a new therapy (eg,
medication) and is remarkably expensive and time-consuming. Forecasting the approval of …