Large language models may pass medical exams with flying colors but using them for diagnoses would currently be grossly negligent. Medical chatbots make hasty diagnoses, do not adhere to guidelines, and would put patients' lives at risk. This is the conclusion reached by a team from the Technical University of Munich (TUM). For the first time, the team has systematically investigated whether this form of artificial intelligence (AI) would be suitable for everyday clinical practice.

A packed auditorium with over 1000 students. This is not a rare sight in introductory informatics lectures. To meet the needs of each individual student under these conditions, Stephan Krusche, professor of Software Engineering, and his team have been building the Artemis learning platform since 2016. It resembles well-known learning platforms, but offers more possibilities.

Researchers at Weill Cornell Medicine have used machine learning to define three subtypes of Parkinson's disease based on the pace at which the disease progresses. In addition to having the potential to become an important diagnostic and prognostic tool, these subtypes are marked by distinct driver genes. If validated, these markers could also suggest ways the subtypes can be targeted with new and existing drugs.

A new study by researchers from the Psychology Department at the Hebrew University have made significant strides in understanding the role of artificial intelligence (AI) in mental health therapy. Their research focuses on the delicate balance between AI-driven interactions and the irreplaceable human touch in therapeutic settings, addressing critical questions about when AI might effectively replace human therapists and when the human connection remains indispensable.

As part of a nationwide trend, many more of NYU Langone Health's patients during the pandemic started using electronic health record tools to ask their doctors questions, refill prescriptions, and review test results. Many patients’ digital inquiries arrived via a communications tool called In Basket, which is built into NYU Langone’s electronic health record (EHR) system, EPIC.

Monitoring of heart rate and physical activity using consumer wearable devices was found to have clinical value for comparing the response to two treatments for atrial fibrillation and heart failure.

The study published in Nature Medicine examined if a commercially-available fitness tracker and smartphone could continuously monitor the response to medications, and provide clinical information similar to in-person hospital assessment.

Cambridge scientists have developed an artificially intelligent (AI) tool capable of predicting in four cases out of five whether people with early signs of dementia will remain stable or develop Alzheimer's disease.

The team say this new approach could reduce the need for invasive and costly diagnostic tests while improving treatment outcomes early when interventions such as lifestyle changes or new medicines may have a chance to work best.