News

The AstroID database allows researchers anywhere to study multiple types of cancer data in one setting.

Johns Hopkins researchers develop a novel neural network with the potential to improve sign language processing.

The sustainable method developed by researchers at Johns Hopkins and Microsoft simulates risks within large language models to prevent harm before they go live.

A massive endeavor including Johns Hopkins researchers and students aims to understand the planet’s most biodiverse habitats.

With her expertise in machine learning, Alexis Battle is working to sift through vast amounts of genetic and clinical data, revealing hidden patterns that can inform treatment strategies and improve patient care.

The Johns Hopkins Sports Analytics Research Group’s innovations were among those featured at the inaugural World Changing Ideas Summit.

Teams co-led by Anqi “Angie” Liu and Tom Lippincott received seed funding to address a broad range of societal and humanitarian challenges through the use of data science and AI.

Researchers Alex Szalay and Janis Taube are pioneering the AstroPath platform, drawing on techniques from astronomy to meticulously map tumor-immune cell interactions in unprecedented detail.

Doctors too busy? AI offers med students real-time expert feedback.

Researchers in the Johns Hopkins Advanced Robotics and Computationally AugmenteD Environments Lab are exploring the use of digital twins to improve surgical workflows.

The researchers are using AI to predict outcomes, individualize treatment, and protect patient privacy, transforming how cancer is understood and treated.

Hopkins researchers bring advanced 3D visualization techniques to neurosurgery.