An advanced algorithm was trained to evaluate more than 100 different details about the inside of a patient's eye. Its ability to identify high-risk patients was comparable to more traditional techniques, exciting researchers. 

When appropriately applied in critical care settings, AI can deliver considerable value to clinical staff, hospital management and local communities. In the process the technology may help resolve persistent staffing shortages.

The pair's hope is that their model, which will first focus on chest X-rays, will provide significant benefits for radiology workflows.

Christoph Wald, MD, vice chair of the American College of Radiology Board of Chancellors, explains the partnerships with academic institutions to create the Health AI Challenge will help provide a better understanding of how foundational AI models work.

Synthetic images are often of diagnostic quality and can be reliably used to assess clinically significant prostate cancer while also sparing patients from contrast exposure.

The collaboration is with Sacramento-based Sutter Health, which operates 24 acute care hospitals across California, employing over 29,000 clinicians. 

The team hopes to develop a model that will estimate a patient's risk of major cardiovascular events and predict when such events are most likely to occur.

Having released the latest version of Llama in December, Meta is telling the world that open-source AI is the future of AI in healthcare.