A machine learning–driven web tool based on 13 standard patient metrics demonstrates strong predictive performance for MASLD, ...

I have come across various ways of defining Artificial Neural Networks (ANNs). Many of them miss a fundamental characteristic ...

Predictive model accelerates the development of nanoparticles as potential drug carriers for targeting neurodegenerative ...

This predictive model built on readily acquired clinical data provides encouraging results for the detection of residual disease. External validation and prospective studies implementing the model in ...

The severity of symptoms in posttraumatic stress disorder (PTSD) varies greatly across individuals in the first year after trauma and it remains difficult to predict whether someone might worsen, ...

The drug development pipeline is a costly and lengthy process. Identifying high-quality "hit" compounds-those with high potency, selectivity, and favorable metabolic properties-at the earliest stages ...

The ability to anticipate what comes next has long been a competitive advantage -- one that's increasingly within reach for developers and organizations alike, thanks to modern cloud-based machine ...

This interesting study adapts machine learning tools to analyze movements of a chromatin locus in living cells in response to serum starvation. The machine learning approach developed is useful, the ...

In the hunt for new therapeutics for cancer and infectious diseases, lasso peptides prove to be a catch. Their knot-like ...

When a company’s data is labeled incorrectly, machine-learning models can't use it correctly. Nvidia wants to patent a ...