Explore how AI in high-throughput screening improves drug discovery through advanced data analysis, hit identification and ...

In a future perhaps not too far away, artificial intelligence and its subfield of machine learning (ML) tools and models, ...

This study highlights non-linear center-of-pressure features that enhance clinical assessment of fall risk in older adults, ...

Training a large artificial intelligence model is expensive, not just in dollars, but in time, energy, and computational ...

The terms get mixed up constantly. In boardrooms, in classrooms, in startup pitches, even in technical documentation.You’ll hear someone say “AI system” when they really mean a predictive model.

A new study by Justin Grandinetti of the University of North Carolina at Charlotte challenges one of the most dominant narratives in artificial intelligence: that modern AI systems are inherently ...

A recent study explored rapid evaporative ionization mass spectrometry (REIMS) as a high-throughput, real-time alternative. By analyzing metabolomic fingerprints from pig neck fat, REIMS was combined ...

Abstract: The increasing prevalence of thyroid disorders necessitates an efficient and reliable system for early diagnosis and classification. Machine learning (ML) offers a promising approach to ...

This study aims to establish an interpretable disease classification model via machine learning and identify key features related to the disease to assist clinical disease diagnosis based on a ...

The development of humans and other animals unfolds gradually over time, with cells taking on specific roles and functions via a process called cell fate determination. The fate of individual cells, ...