Using generative AI to design, train, or perform steps within a machine-learning system is risky, argues computer scientist Micheal Lones in a paper appearing in Patterns. Though large language models ...

Analysis of the 191 samples shows that 55 percent of groundwater falls within low to no restriction categories for irrigation ...

A skin cancer diagnosis can seem to arrive out of nowhere. But buried in years of health records, prescription histories, and ...

Read more about AI can’t deliver climate gains without strong governance and capacity building on Devdiscourse ...

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

Innovative machine learning models using routine clinical data offer superior stroke risk prediction in atrial fibrillation, ...

This study develops a high-accuracy machine-learning framework to predict and optimize metal-doped MnO2 cathodes for aqueous ...

RESEARCHERS reported that new transcranial magnetic stimulation (TMS) biomarkers, combined with machine learning, accurately distinguished individuals with major depressive disorder (MDD) from healthy ...

ABSTRACT: Accurate prediction of survey response rates is essential for optimizing survey design and ensuring high-quality data collection. Traditional methods often struggle to capture the complexity ...

Monoclonal antibody (mAb) manufacturing must continually improve to keep up with increasing demands. To do this, biomanufacturers can deploy machine learning tools to augment traditional process ...

ABSTRACT: The accurate prediction of backbreak, a crucial parameter in mining operations, has a significant influence on safety and operational efficiency. The occurrence of this phenomenon is ...

MASLD is prevalent in T2DM patients, with a 65% occurrence rate, and poses a higher risk for severe liver diseases. The study analyzed 3,836 T2DM patients, identifying key predictors like BMI, ...