University researchers have pioneered a new tool to determine the risk of secondary heart attacks in cancer patients using Artificial Intelligence (AI).

Cancer patients who suffer a heart attack face increased risks because of their weakened cardiovascular system. This means they are more likely to die, bleed or experience another serious cardiovascular event.

Aston University and BioCare Ltd are working together to create a unique AI-powered digital health tool that can deliver personalised nutritional and lifestyle advice by analysing data from health tests and questionnaires.

Along with ongoing support, the app will empower its users to make long-term and lasting improvements to their health and wellbeing.

Prediabetes is an extremely heterogeneous metabolic disorder. Scientists from several partner institutes of the German Center for Diabetes Research (DZD) have now used artificial intelligence (AI) to identify epigenetic markers that indicate an elevated risk of complications. A simple blood test could be sufficient to identify individuals at high risk of developing type 2 diabetes and its complications at an early stage. The study shows how data-driven approaches and molecular medicine interact in the diagnostic process.

A new medical large language model (LLM) achieved over 91 percent accuracy in identifying female participants diagnosed with major depressive disorder after analyzing a short WhatsApp audio recording where participants described their week, according to a study published in the open-access journal PLOS Mental Health by Victor H. O. Otani, from Santa Casa de São Paulo School of Medical Sciences and Infinity Doctors Inc., Brazil, and colleagues.

From a physiological perspective, heartbeats and breathing do not operate independently in the human body. Cardiac rhythm varies with the respiratory cycle, and the close interaction between the two is known as cardiopulmonary coupling (CPC). CPC reflects the regulatory state of the autonomic nervous system and serves as an important physiological indicator for evaluating sleep quality, cardiovascular health, and stress levels.

DiaCardia, a novel artificial intelligence model that can accurately identify individuals with prediabetes using either 12-lead or single-lead electrocardiogram (ECG) data, has been recently developed. This breakthrough holds promise for future home-based prediabetes screening using consumer wearable devices, without requiring invasive blood tests. This study emphasizes the utility of the ECG as a powerful biomarker and highlights that the innovative AI model can contribute to the prevention of diabetes.

A new artificial intelligence (AI) method called BioPathNet helps researchers systematically search large biological data networks for hidden connections - from gene functions and disease mechanisms to potential therapeutic approaches. BioPathNet was developed by teams at Helmholtz Munich and Mila - Quebec Artificial Intelligence Institute in Montreal, Canada. The researchers are now presenting the method in the journal Nature Biomedical Engineering.