Graph Transformer for Drug Response Prediction.

Previous models have shown that learning drug features from their graph representation is more efficient than learning from their strings or numeric representations. Furthermore, integrating multi-omics data of cell lines increases the performance of drug response prediction. However, these models have shown drawbacks in extracting drug features from graph representation and incorporating redundancy information from multi-omics data.

Prevalence, Awareness, Treatment, and Control of High Blood Pressure: A Population-Based Survey in Thai Nguyen, Vietnam.

Background: Cardiovascular disease (CVD) is one of the leading causes of morbidity and mortality in Vietnam and hypertension (HTN) is an important and prevalent risk factor for CVD in the adult Vietnamese population. Despite an increasing prevalence of HTN in this country, information about the awareness, treatment, and control of HTN is limited. The objectives of this study were to describe the prevalence, awareness, treatment, and control of HTN, and factors associated with these endpoints, in residents of a mountainous province in Vietnam.