Northwestern University researchers have developed a first-of-its-kind small, flexible, stretchable bandage that accelerates healing by delivering electrotherapy directly to the wound site.

In an animal study, the new bandage healed diabetic ulcers 30% faster than in mice without the bandage.

Millions of people suffer from these painfully common conditions, and often endure inconvenient and invasive medical procedures to diagnose the causes.

In a study published in Nature Electronics, Khalil B. Ramadi, Assistant Professor of Bioengineering at NYU Tandon School of Engineering, revealed that he and a team of collaborators at MIT and Caltech have developed a tiny pill-like electromagnetic device that,

The EU has awarded a 6.55 million EUR funding to a HUS Helsinki University Hospital-led consortium to examine the mechanisms behind the long-term effects of a COVID-19 infection. The objective is also to create a Decision support system for prediction and management of Long Covid Syndrome (LCS).

A new smartphone application called FAST.AI may help people who are having a stroke or their family and caregivers recognize common stroke symptoms in real time, prompting them to quickly call 9-1-1, according to preliminary research to be presented at the American Stroke Association's International Stroke Conference 2023.

Researchers at the University of Sussex are using Artificial Intelligence (AI) technology to analyse different types of cancer cells to understand different gene dependencies, and to identify genes that are critical to a cell's survival. Sussex researchers have done this by developing a prediction algorithm that works out which genes are essential in the cell, by analysing the genetic changes in the tumour.

Scientists at University of California San Diego School of Medicine have developed an artificial intelligence (AI)-based strategy for discovering high-affinity antibody drugs.

In the study, published January 28, 2023 in Nature Communications, researchers used the approach to identify a new antibody that binds a major cancer target 17-fold tighter than an existing antibody drug.

New machine learning research led by Professor Farrokh Alemi and Professor Janusz Wojtusiak provides a way for patients and clinicians to better predict whether symptoms are due to COVID-19, influenza, or RSV. A more accurate diagnosis leads to better decisions on course of care to heal patients and prevent the disease from spreading.