Research

Ear Sensor Enables Safe Telemedical Care for COVID-19 Risk Patients

Using telemedicine, COVID-19 patients can be cared for safely at home - from initial home isolation to recovery or, in case problems arise, admission to hospital. A team from the Technical University of Munich (TUM) has now successfully demonstrated this in a study involving 150 patients with risk factors for a severe progression of the disease.

Scientists Show How AI may Spot Unseen Signs of Heart Failure

A special artificial intelligence (AI)-based computer algorithm created by Mount Sinai researchers was able to learn how to identify subtle changes in electrocardiograms (also known as ECGs or EKGs) to predict whether a patient was experiencing heart failure.

Artificial Intelligence-Based Technology Quickly Identifies Genetic Causes of Serious Disease

An artificial intelligence (AI)-based technology rapidly diagnoses rare disorders in critically ill children with high accuracy, according to a report by scientists from University of Utah Health and Fabric Genomics, collaborators on a study led by Rady Children’s Hospital in San Diego.

A Cryptography Game-Changer for Biomedical Research at Scale

Predictive, preventive, personalized and participatory medicine, known as P4, is the healthcare of the future. To both accelerate its adoption and maximize its potential, clinical data on large numbers of individuals must be efficiently shared between all stakeholders. However, data is hard to gather. It’s siloed in individual hospitals, medical practices, and clinics around the world.

Brain Cell Differences could be Key to Learning in Humans and AI

The new study found that by tweaking the electrical properties of individual cells in simulations of brain networks, the networks learned faster than simulations with identical cells.

They also found that the networks needed fewer of the tweaked cells to get the same results, and that the method is less energy intensive than models with identical cells.

Time until Dementia Symptoms Appear can be Estimated via Brain Scan

Researchers at Washington University School of Medicine in St. Louis have developed an approach to estimating when a person who is likely to develop Alzheimer’s disease, but has no cognitive symptoms, will start showing signs of Alzheimer's dementia.

The algorithm, available online in the journal Neurology, uses data from a kind of brain scan known as amyloid positron emission tomography (PET) to gauge brain levels of the key Alzheimer's protein amyloid beta.

Study Shows Trust is still at Heart of NHS COVID App Reluctance

A new study has shown that issues surrounding trust are still at the heart of people's reluctance to download and use the NHS App, particularly among Black, Asian and minority ethnic (BAME) communities.

Researchers from the University of Nottingham's Horizon Digital Research Institute and the Trustworthy Autonomous Systems (TAS) Hub undertook a survey of

More eHealth News ...