Predictive Oncology Inc. announced the successful development of predictive models for 21 unique compounds sourced from the University of Michigan's Natural Products Discovery Core, marking a ...

Huge libraries of drug compounds may hold potential treatments for a variety of diseases, such as cancer or heart disease. Ideally, scientists would like to experimentally test each of these compounds ...

Researchers at the CUNY Graduate Center have created an artificial intelligence model, Context-aware Deconfounding Autoencoder (CODE-AE), that can screen drug compounds to accurately predict efficacy ...

A research team has created an artificial intelligence model that could significantly improve the accuracy and reduce the time and cost of the drug development process. The new model, called CODE-AE, ...

Antibiotic resistance is turning routine infections into life threatening events, and the traditional pipeline for new drugs is not keeping up. In response, laboratories are handing a growing share of ...

Researchers have devised a new machine learning method to improve large-scale climate model projections and demonstrated that the new tool makes the models more accurate at both the global and ...

A slide and compound drilling model calculates build-up rate (BUR) of a single bent-angle motor assembly using a physical model and genetic-algorithm back propagation (GA-BP) regression analysis. A ...

AI needs human data to function effectively, but the internet is becoming flooded with AI-generated content. Artificial intelligence has revolutionized everything from customer service to content ...