1+ hour, 48+ min ago  (1017+ words) In this interview, industry expert Dr. Anthony Grice explains how machine learning predicts LC-MS response factors, reducing reliance on surrogates, improving accuracy, and accelerating extractables analysis and risk assessment workflows When you detect an unknown chemical in an E&L…...

1+ week, 1+ day ago  (800+ words) JMIR Publications today released a report on developments in the evidence gap in drug safety during pregnancy in its News and Perspectives section. Machine learning can help close pregnancy drug safety gaps JMIR Publications today released a report on developments…...

1+ week, 3+ day ago  (262+ words) News-Medical Artificial intelligence models show high accuracy in cardiac care Cardiac arrest remains one of the most urgent and unforgiving medical emergencies, where every minute can determine survival and neurological recovery. Traditional care depends on rapid recognition, high-quality cardiopulmonary resuscitation,…...

4+ week, 2+ day ago  (1235+ words) Chemists and computer scientists tapped AI to find new disinfectants to combat the growing threat of dangerous "superbugs." The method yielded 11 new QACs that show activity against antimicrobial-resistant bacteria. We believe this is the first example of using AI to…...

1+ mon, 1+ hour ago  (527+ words) By combining large-scale genetics with machine learning, researchers uncover hidden risk patterns and distinct patient subtypes that could transform how type 1 diabetes is identified and understood. Study: Genetic association and machine learning improve the prediction of type 1 diabetes risk. Image…...

9+ mon, 3+ week ago  (531+ words) When cells expire, they leave behind an activity log of sorts: RNA expelled into blood plasma that reveal changes in gene expression, cellular signaling, tissue injury and other biological processes. The findings were published Aug. 11 in Proceedings of the National…...

6+ mon, 4+ week ago  (109+ words) Furthermore, it demonstrated practicality in "chronological validation," which alerts users to drugs facing market withdrawal due to toxicity. After training the prediction model on only drug data up to 1991, it correctly predicted drugs expected to be withdrawn from the market…...

7+ mon, 4+ week ago  (146+ words) The work is published in'Nature Computational Science'and was co-led by SEAS graduate student Ryan Krueger and former NSF-Simons Quant Bio Fellow'Krishna Shrinivas, now an assistant professor at Northwestern, in collaboration with'Michael Brenner, the Catalyst Professor of Applied Mathematics and Applied…...

8+ mon, 2+ week ago  (236+ words) A new study published in JCO Clinical Cancer Informatics demonstrates that machine learning models incorporating patient-reported outcomes and wearable sensor data can predict which patients with non'small cell lung cancer are most at risk of needing urgent care during treatment....

8+ mon, 2+ week ago  (405+ words) Artificial intelligence is transforming emergency medicine by enhancing triage, diagnosis, and resource management, while also facing challenges related to ethics, bias, and regulation. This article explores its applications, benefits, and limitations in real-world clinical care. The emergency patient journey and…...