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,

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.

Cancer has many faces - no wonder, then, that the range of cancer-causing mutations is huge as well. The totality of such genomic alterations in an individual is what experts call a "mutational landscape." These landscapes differ from one another depending on the type of cancer. And even people suffering from the same cancer often have different mutation patterns.

To help the estimated 1.45 million Americans living with type 1 diabetes better manage their blood sugar levels, Oregon Health & Science University is combining the power of an artificial intelligence-driven smartphone app with the support of human experts.

The Leona M. and Harry B. Helmsley Charitable Trust has awarded OHSU more than $4.3 million to support this work.