Rajesh Patil and Professor Magnus Löfstrand have developed an AI system that detects welding defects, reduces material waste, ...

As genAI spreads into core systems, weak governance, hidden bias and security gaps threaten trust, compliance and long-term business value ...

Dr Michele Orini shares how machine learning can help identify critical VT ablation targets for a safer, data-driven ...

This is the Best of the Week. Voices from the Analytical Front Line: Bingchuan Wei on Chromatography in 2026 In the year 2026, chromatography is undergoing a series of advancements and challenges.

The core idea of LCQHNN is to center on quantum feature amplification (Quantum Feature Amplification) while combining a classical stability optimization strategy, establishing an efficient information ...

A recent analysis of a major developmental dataset reveals that children who play musical instruments over several years ...

Learn how ECG noise filtering that adapts to noise type improved QT and QRS accuracy and supports more reliable cardiac ...

Scientists are trying to tame the chaos of modern artificial intelligence by doing something very old fashioned: drawing a table. Instead of chemical elements, the new chart arranges learning ...

ABSTRACT: From the perspective of student consumption behavior, a data-driven framework for screening student loan eligibility was developed using K-means clustering analysis and decision tree models.

In this project, We build a Support Vector Machines classifier to classify a Pulsar star. We have used the Predicting a Pulsar Star dataset for this project. We have downloaded this dataset from the ...

The stroke deprives person's brain of oxygen and nutrients, which can cause brain cells to die. Numerous works have been carried out for predicting various diseases by comparing the performance of ...