The use of large language models (LLMs) and other forms of generative AI (GenAI) in healthcare has surged in recent years, and many of these technologies are already applied in clinical settings. As such, they often qualify as medical devices and must comply with specific laws and regulatory frameworks. Recent decisions have shown that approval is possible for applications with narrowly defined tasks.

Scientists have used an AI model to reassess the results of a completed clinical trial for an Alzheimer’s disease drug. They found the drug slowed cognitive decline by 46% in a group of patients with early stage, slow-progressing mild cognitive impairment - a condition that can progress to Alzheimer’s.

Using AI allowed the team to split trial participants into two groups: either slowly or rapidly progressing towards Alzheimer’s disease.

An AI model trained to detect abnormalities on breast MR images accurately depicted tumor locations and outperformed benchmark models when tested in three different groups, according to a study published today in Radiology, a journal of the Radiological Society of North America (RSNA).

"AI-assisted MRI could potentially detect cancers that humans wouldn’t find otherwise," said the study's lead investigator Felipe Oviedo, Ph.D., a senior research analyst at Microsoft's AI for Good Lab.

Artificial intelligence (AI) models such as ChatGPT are designed to rapidly process data. Using the AI ChatGPT-4 platform to extract and analyze specific data points from the Magnetic Resonance Imaging (MRI) and computed tomography (CT) scans of patients with pancreatic cysts, researchers found near-perfect accuracy when compared directly against the manual approach of chart review performed by radiologists, according to a study published in the Journal of the American College of Surgeons (JACS).

Snake, scorpion, and spider venom are most frequently associated with poisonous bites, but with the help of artificial intelligence, they might be able to help fight antibiotic resistance, which contributes to more than one million deaths worldwide each year.

In a study published in Nature Communications, researchers at the University of Pennsylvania used a deep-learning system called APEX to sift through a database

Before an important meeting or when a big decision needs to be made, we often mentally run through various scenarios before settling on the best course of action. But when it comes to our health - be it choosing a treatment for an ailment or even selecting a dietary regimen - it is a lot harder to predict how each choice will affect our bodies and whether it will suit us personally.

The new study exposes the dangerous flaws in using artificial intelligence (AI) chatbots for mental health support. For the first time, the researchers evaluated these AI systems against clinical standards for therapists.