A new study from Mass General Brigham has found that large foundation models that incorporate a richer level of details may mitigate disparities between different demographic groups and enhance model security. Corresponding author Faisal Mahmood, PhD, of the Division of Computational Pathology in the Department of Pathology at Mass General Brigham referred to the findings as a "call to action" for scientists and regulators to utilize diverse data sets in research to benefit all patient groups. Find details in the news story below.
Patients with end-stage heart failure may benefit from a heart transplant. Many patients, unfortunately, suffer from organ transplant rejection, which occurs when the immune system destroys the donated organ. However, diagnosing transplant rejection is difficult.
Heart transplantation can be lifesaving for patients with end-stage heart failure. However, many patients experience organ transplant rejection, in which the immune system attacks the transplanted organ. But detecting transplant rejection is challenging. In its early stages, patients may not experience symptoms, and experts do not always agree on the degree and severity of the rejection when they examine heart biopsies to diagnose the problem.
An artificial-intelligence system shows promise in identifying signs of heart transplant rejection miragenews.com - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from miragenews.com Daily Mail and Mail on Sunday newspapers.