Beef tallow, seed oils, and full-fat dairy: Are any of them heart-healthy? - Harvard Health

Case: In a patient diagnosed with metastatic clear cell RCC, foci observed at very low levels on 18F-FDG PET/CT, and some that were not detectable at all, were seen as dramatically dense on [68Ga]Ga-DPI-4452-PET/CT (carbonic anhydrase IX receptor) imaging. Image courtesy of Prof. Arslan Research was presented at the 39th Annual Congress of the European Association of Nuclear Medicine (EANM’26)

When analyzed by a new artificial intelligence model developed at Penn Medicine, CT scans reveal much about a patient's health beyond the specific condition they were originally ordered for, according to a new study published in NPJ Digital Medicine. The AI model, dubbed Percival, can uncover nearly hidden patterns in disease and potential future health risks that might have otherwise gone unnoticed by human eyes. While other models may need to be directed to find certain health conditions or outcomes, Percival can effectively run in the background to pick up what is unseen. Our teams have developed something that learns broadly from imaging data and uncovers connections between scans, lab values, people's physiology, and clinical outcomes to potentially give more accurate assessments of health, or even ring alarm bells early. This is work that points toward a future in which medical imaging becomes a foundation for more personalized and proactive healthcare. "