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, ...

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 ...

This week is World Health Organization’s (WHO) World Antimicrobial Resistance (AMR) Awareness Week, bringing attention to the urgent need for new antibacterial drugs. A new study reports that ...

IIIF provides researchers rich metadata and media viewing options for comparison of works across cultural heritage collections. Visit the IIIF page to learn more. This is a model of an early design ...

You may not be familiar with hydrogen sulfide, a colorless gas that smells like rotten eggs, and is produced naturally from decaying matter. However, this gas is lethal to breathe in, and hydrogen ...

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 ...