Research led by the University of Plymouth has shown that a new deep learning AI model can identify what happens and when during embryonic development, from video.

Published in the Journal of Experimental Biology, the study highlights how the model, known as Dev-ResNet, can identify the occurrence of key functional developmental events in pond snails, including heart function, crawling, hatching and even death.

Since the launch of ChatGPT 3 in November 2022, we've been abuzz with talk of artificial intelligence: is it an unprecedented opportunity, or will it rob everyone of jobs and creativity? As we debate on social media (and perhaps use ChatGPT almost daily), generative AIs have also entered the arena of university communication. These tools - based on "Large Language Models" that were optimized for interactive communication - can indeed support, expand, and innovate university communication offerings.

A groundbreaking study published in Health Data Science, a Science Partner Journal, introduces a curated bibliographic dataset that aims to revolutionize the landscape of Health Artificial Intelligence (AI) research. Led by Xuanyu Shi and Jian Du from Peking University, this dataset integrates a vast array of Health AI-related documents, offering an invaluable resource for researchers, policymakers, and practitioners.

Generative artificial intelligence (AI), such as GPT-4, can help predict whether an emergency room patient needs to be admitted to the hospital even with only minimal training on a limited number of records, according to investigators at the Icahn School of Medicine at Mount Sinai. Details of the research were published in the online issue of the Journal of the American Medical Informatics Association.

A new advanced artificial intelligence (AI) algorithm may lead to better - and earlier - predictions and novel therapies for autoimmune diseases, which involve the immune system mistakenly attacking their body’s own healthy cells and tissues. The algorithm digs into the genetic code underlying the conditions to more accurately model how genes associated with specific autoimmune diseases are expressed and regulated and to identify additional genes of risk.

In an ischaemic stroke, an artery in the brain is blocked by blood clots and the brain cells can no longer be supplied with blood as a result. Doctors must therefore act quickly and unblock the artery with the help of catheters. During the so-called mechanical thrombectomy, a lot of data has to be recorded and then transferred to various registers.

UVA Health researchers have developed a powerful new risk assessment tool for predicting outcomes in heart failure patients. The researchers have made the tool publicly available for free to clinicians.

The new tool improves on existing risk assessment tools for heart failure by harnessing the power of machine learning (ML) and artificial intelligence (AI) to determine patient-specific risks of developing unfavorable outcomes with heart failure.