Penn Engineers have developed PeptiVerse, an AI-powered platform that predicts key chemical and biological properties of peptides, the strings of amino acids whose medical potential has been demonstrated by the success of GLP-1 drugs, the widely used weight-loss treatments.

In Nature Communications, the researchers describe how they trained PeptiVerse using a wide range of data sets, allowing it to predict properties that can help determine whether a peptide is worth pursuing as a potential drug,

A UVA Health emergency medicine doctor and colleague at Clemson University have developed a framework to help hospitals integrate artificial intelligence (AI) to not just increase efficiency and cut costs but ensure high-quality patient care remains the top priority.

With the massive potential of artificial intelligence to transform healthcare in the coming years, UVA’s R. Andrew Taylor, MD, MHS, and Clemson’s Arwen B.L. Declan, MD, PhD, created the new framework to ensure healthcare remains “rooted in its ethical obligations”

Researchers have built a tool to uncover hidden issues in the massive datasets used to train medical AI.

The tool searches training data for subtle patterns that could lead AI models to incorrect conclusions, potentially jeopardizing patient care. The work aims to help researchers and regulators make artificial intelligence more reliable and trustworthy for real-world clinical use.

Artificial intelligence (AI) is rapidly improving scientists’ ability to detect chemicals in the environment and human body. A new perspective article argues that the next major step is not simply identifying more chemicals, but determining which exposures are most likely to disrupt biological systems and contribute to disease.

Published in Artificial Intelligence & Environment, the article describes a shift toward functional chemical exposomics,

Patient trust in medical professionals might hinge on what artificial intelligence (AI) has to say, according to a team led by Penn State researchers.

Using an AI chatbot roleplaying as a human doctor, the team identified how people perceive medical professionals when they think a “human” doctor consults an AI system for a second opinion during mental health consultations.

Researchers have developed a new method that enables human cells to be programmed to perform calculations and make autonomous decisions, similar to how computer chips function, which could help scientists build smarter cell-based treatments for diseases, like cancer, in the future.

In a new study published in Nature Communications, Ph.D. student Keren Roas and Dr. Lior Nissim from the Hebrew University of Jerusalem Institute for Medical Research Israel-Canada, Faculty of Medicine, created artificial genetic systems inside human cells that can process information and follow complex instructions.

Artificial intelligence (AI) is helping nurses better predict health problems before they become emergencies, according to a new review of existing research published in JMIR Nursing. The study found that AI-based nursing interventions can improve the care of people living with chronic illnesses by identifying patients at greater risk of complications, reducing unplanned hospital visits, and potentially lowering health care costs.