Machine learning enhances proteomics by optimizing peptide identification, structure prediction, and biomarker discovery.

Background Patients with heart failure (HF) frequently suffer from undetected declines in cardiorespiratory fitness (CRF), which significantly increases their risk of poor outcomes. However, current ...

Scientists have developed a new way to help understand what happens in the body when people consume a plant product and the ...

Modelling the Subjective Road Traffic Noise Annoyance Levels in Nairobi City, Kenya. World Journal of Engineering and ...

Objective This study aims to evaluate relationships between self-reported fine motor ability and quality of life (assessed by life satisfaction and life problems) from people with spinal cord injury ...

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...

Objective To determine whether liquefied petroleum gas (LPG) can reduce perinatal mortality in a setting with high reliance on biomass fuels for cooking.Design Community-based two-arm parallel cluster ...

Abstract: The past decade has witnessed the success of deep learning-based multivariate time-series forecasting in Internet of Things (IoT) systems. However, dynamic variable correlation remains a ...

Current models of mortality risk after heart failure (HF) rely primarily on cardiac-specific clinical variables and may underestimate risk in elderly East Asian patients. Researchers from Japan used ...

Background Gut microbiota dysbiosis is linked to autism spectrum disorder (ASD) in children. However, the role of bacterial ...

As the population ages, China will face an ever-increasing burden from CS. Strategies targeting elder population and high-risk groups should be prioritized in the establishment of management related ...