#biomedical-visualization

#biomedical-visualization

"I would like to sincerely apologise to any patients who have been affected and recalled for a scan as I understand receiving such news can be unsettling."

As the Magerstadt Professor of Cardiovascular Epidemiology, Khan studies the epidemiology of risk for heart failure. Using population-based cohorts and large electronic health record data analyses, she performs mechanistic studies that may enhance risk prediction and identify novel therapeutic agents for the prevention and treatment of cardiovascular disease. Khan and her team have developed a tool to predict risk and prevent cardiovascular disease such as heart failure, stroke, arrhythmia, coronary artery disease and many other conditions.

The large volume of abdominal computed tomography (CT) scans coupled with the shortage of radiologists have intensified the need for automated medical image analysis tools. Previous state-of-the-art approaches for automated analysis leverage vision-language models (VLMs) that jointly model images and radiology reports.

The human brain is complex. Artificial intelligence (AI) machine learning and medical imaging data are accelerating breakthroughs in brain health, especially in medical diagnostics. A peer-reviewed study published today in Nature Neuroscience unveils an AI foundation model called BrainIAC (Brain Imaging Adaptive Core) that is capable of predicting brain age, dementia, time-to-stroke, and brain cancer from brain magnetic resonance imaging (MRI).

AI plays an important role-but not by fixing fragmented data on its own. The work of organizing, connecting, and interpreting healthcare information still belongs to people and the systems they build. Where AI helps is after that foundation is in place: by bringing the right information forward at the right time, reducing the effort it takes to find what matters, and supporting better decisions in the moment of care.

Anais Muczynski, 36, an orthoptist who lives with her husband Vincent Muczynski, 41, a researcher, received her primary breast cancer diagnosis in January 2023 after discovering a quail egg-sized lump in her left breast. At the time, the London-based couple were "optimistic", as it was stage one meaning the cancer was only in the breast tissue or in the lymph nodes close to the breast and she underwent chemotherapy, immunotherapy, and a double mastectomy.

When Dr. Homoud Aldahash started the three-hour process of removing a tumor about the size of a walnut from a patient's brain, it was an experience unlike any other in his 25 years as a neurosurgeon. It wasn't Aldahash's gloved hands slicing 68-year-old Mohammed Almutrafi's right frontal lobe, but surgical instruments attached to a set of robotic arms, which Aldahash controlled from a console where he sat three meters away.