Through the use of eHealth application ikHerstel, patients recover from major abdominal operations 30% faster than patients who do not use the app. That is the main conclusion of research led by Amsterdam UMC across eleven Dutch hospitals. The app aims to empower patients to feel more in control of their recovery process. The results were published today in Lancet Digital Health.

New research led by scientists working with Georgia State University's TReNDS Center has identified age-related changes in brain patterns associated with the risk for developing schizophrenia.

The discovery could help clinicians identify the risk for developing mental illness earlier and improve treatment options. The study is published in the Proceedings of the National Academy of Sciences (PNAS).

When you need accurate information about a serious illness, should you go to Google or ChatGPT?

An interdisciplinary study led by University of California, Riverside, computer scientists found that both internet information gathering services have strengths and weaknesses for people seeking information about Alzheimer's disease and other forms of dementia.

It is possible to accurately predict hospital admission numbers due to COVID-19 up to four weeks in advance using an Artificial Intelligence (AI) based system together with COVID wastewater sampling, new research shows.

The study, published in the journal Nature Communications, used wastewater data from 159 counties in the US, covering nearly 100 million Americans, along with US hospital admission records, to develop the prediction model.

Artificial intelligence (AI) is already being used to diagnose skin cancer, but it cannot (yet) keep pace with the complex decision-making of doctors in practice. An international research team led by Harald Kittler of MedUni Vienna has now explored a learning method in which greater accuracy in AI results can be achieved by incorporating human decision-making criteria.

Statistics indicate that globally 1 in 4 adults over the age of 25 will have a stroke in their lifetime. One of the most serious consequences of this disease is disability. The joint study by Rytis Maskeliūnas, a researcher at Kaunas University of Technology, Faculty of Informatics (KTU IF), and Lithuanian researchers is focused on creating an artificial intelligence (AI)-based system that aims to facilitate the rehabilitation process.

Artificial intelligence (AI) can use data from low-dose CT scans of the lungs to improve risk prediction for death from lung cancer, cardiovascular disease and other causes, according to a study published in Radiology, a journal of the Radiological Society of North America (RSNA).