In a groundbreaking study published on January 18, 2024, in Cancer Discovery, scientists at University of California San Diego School of Medicine leveraged a machine learning algorithm to tackle one ...

Antimicrobials are naturally derived or synthetically designed chemicals, including antibiotics, antivirals, antifungals, and antiparasitics, used to prevent and treat infectious diseases in humans, ...

Antimicrobial resistance (AMR) is an increasingly dangerous problem affecting global health. In 2019 alone, methicillin-resistant Staphylococcus aureus (MRSA) accounted for more than 100,000 global ...

Machine learning identified RDW and HGB as key predictors of hydroxyurea resistance in polycythemia vera, aiding early identification and treatment adjustment. The PV-AIM study used electronic health ...

Antibiotic resistance continues to be a worldwide problem. Researchers are use AI computer modeling to help design new compounds. The Conversation — Antibiotic resistance is a growing public health ...

Researchers analyzed the genomes of hundreds of malaria parasites to determine which genetic variants are most likely to confer drug resistance. Researchers at University of California San Diego ...

Discovering effective drug combinations may now be easier thanks to a screening platform made public today by St. Jude Children's Research Hospital scientists. Many diseases, including cancers, ...

The research, published in Nature Communications, aims to improve drug safety and effectiveness by accounting for genetic ...

Understanding and preventing drug side effects holds a profound influence on drug development and utilization, profoundly impacting patients’ physical and mental well-being. Traditional artificial ...