Clustering has primarily been used as an analytical technique to group unlabeled data for
extracting meaningful information. The fact that no clustering algorithm can solve all …

Abstract Machine learning (ML) has been increasingly used to aid aerodynamic shape
optimization (ASO), thanks to the availability of aerodynamic data and continued …

Background Ambient air pollution is a major environmental cause of morbidity and mortality
worldwide. Cities are generally hotspots for air pollution and disease. However, the exact …

Clustering, a traditional machine learning method, plays a significant role in data analysis.
Most clustering algorithms depend on a predetermined exact number of clusters, whereas …

The increasing access to health data worldwide is driving a resurgence in machine learning
research, including data-hungry deep learning algorithms. More computationally efficient …

Cluster analyzes have been widely used in mental health research to decompose inter-
individual heterogeneity by identifying more homogeneous subgroups of individuals …

Background Food adulteration became a potential threat to the food industries and human
health. The conventional laboratory techniques are time and cost intensive, require sample …

Precision medicine uses genetic, environmental and lifestyle factors to more accurately
diagnose and treat disease in specific groups of patients, and it is considered one of the …

Background How to timely identify the food quality through a low-cost, easy operation, and
high-throughput way is a milestone protects for food industry, especially in resource-limited …

Plant function is the result of the concerted action of single cells in different tissues.
Advances in RNA-seq technologies and tissue processing allow us now to capture …