Attention-deficit/hyperactivity disorder (ADHD) affects millions of children, yet many go years without a diagnosis, missing the chance for early support that can change long-term outcomes even when early signs are present.

In a new study, Duke Health researchers found that artificial intelligence tools can analyze routine electronic health records to accurately estimate a child’s risk of developing ADHD years before a typical diagnosis.

Digital transformation and artificial intelligence (AI) in healthcare requires a range of safeguards and standards to work well, but new research from Flinders University provides support for effective AI systems to improve cardiovascular care.

The study examines how Clinical Decision Support Systems (CDSS) can transform cardiovascular disease management - a leading cause of death in Australia - by providing more accurate, timely decisions while addressing real-world barriers like workflow integration, usability and clinician adoption.

Researchers at McMaster University have developed a new generative artificial intelligence (AI) model capable of drastically speeding up drug discovery - and, in early tests, it has already designed a brand-new antibiotic.

The discovery is a demonstration of how AI could dramatically improve the slow and costly search for new antimicrobial medicines, as bacteria and other microbes continue to evolve resistance to our current suite of drugs.

Oregon Health & Science University researchers have developed a first-of-its-kind method to predict cancer patient survival using advanced molecular data from individual cells.

Survival analysis is central to clinical oncology. Modern cancer studies can now measure gene activity in single cells from a patient’s tumor and link this information to how long patients live.

There may be some truth to the saying "the eyes are the window to the soul." Age-related changes are reflected in the retina, the light-sensitive tissue at the back of the eye. Recent research shows that a photo of the retina may also reveal potential risks for major diseases like diabetes. A research group led by Professor Toru Nakazawa at the Tohoku University Graduate School of Medicine has developed an artificial intelligence (AI) model that estimates "retinal age,"

Artificial intelligence (AI) is transforming breast cancer care by improving diagnosis, treatment planning, and drug development. AI technologies, particularly deep learning (DL) and machine learning (ML), are enhancing screening efficiency, reducing errors, and aiding in personalized treatment decisions. With the ability to analyze large datasets, AI is revolutionizing how breast cancer is detected and managed, leading to better outcomes for patients.

University of Virginia School of Medicine scientists have developed a bold new approach to drug development and discovery that could dramatically accelerate the creation of new medicines.

UVA’s Nikolay V. Dokholyan, PhD, and colleagues have developed a suite of artificial intelligence-powered tools, called YuelDesign, YuelPocket and YuelBond, that work together to transform how new drugs are created.