This research aims to reactivate object-oriented databases using intelligent tools to improve performance and accuracy in ...

One of the shared, fundamental goals of most chemistry researchers is the need to predict a molecule's properties, such as ...

What began as a Ph.D. project has grown into a website with 120,000 unique visitors each year. With the platform OpenML, ...

A new data-driven technique for obstacle avoidance in autonomous vehicles is reported in the International Journal of Vehicle ...

Sepsis is a life-threatening condition caused by organ dysfunction resulting from the body's dysregulated response to ...

Through large-scale cohort analysis, researchers have established a novel and stable classification of sepsis patients. Multi ...

Flood modeling in arid environments like Saudi Arabia is constrained by the absence of reliable hydrological datasets and ...

MNEs are increasingly using algorithmic tools in TP. Sahasranshu Dash argues that data ethics should therefore plug directly ...

An experimental study shows that already small-scale quantum computers can boost the performance of machine learning algorithms.

One of the current hot research topics is the combination of two of the most recent technological breakthroughs: machine learning and quantum computing. An experimental study shows that already ...

SAVANA uses a machine learning algorithm to identify cancer-specific structural variations and copy number aberrations in long-read DNA sequencing data. The complex structure of cancer genomes ...

Clustering can be done using various algorithms such as k-means, hierarchical clustering, density-based spatial clustering of applications with noise (DBSCAN) and Gaussian mixture model (GMM) ...