A machine learning model predicted cardiac tamponade during AF ablation with high accuracy. Learn how XGBoost may improve ...

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk ...

Generative AI is maturing but remains a disruptive, sometimes divisive, force.

Researchers used 16S rRNA sequencing and machine learning to identify gut microbiome patterns associated with insulin resistance severity in people with type 2 diabetes. XGBoost models showed that ...

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and ...

As Raipur expands, the Kharun River Basin faces intensifying floods and sediment loads. Explore how climate change and ...

This study presents a bio-inspired control framework for soft robots, enhancing tracking accuracy by over 44% under disturbances while maintaining stability.

In the first instalment of LCGC International's interview series exploring how artificial intelligence (AI)/machine learning ...

A physics informed machine learning model predicts thermal conductivity from infrared images in milliseconds, enabling fast, ...

For riders dedicated to conquering steep gradients, the equipment of choice is the Climbing Carbon Wheelset, a specialized ...

BACKGROUND: Mental stress-induced myocardial ischemia is often clinically silent and associated with increased cardiovascular risk, particularly in women. Conventional ECG-based detection is limited, ...