The discoveries, detailed in the June 11 online issue of Nature Genetics, reveal genetic factors impacting heart disease that open new avenues for targeted treatments and personalized approaches to cardiovascular care.
Like many conditions, epilepsy treatment starts with early detection.
Mammography successfully reduces breast cancer mortality, but also carries the risk of false-positive findings. In recent years, researchers have studied the use of AI systems in screening.
Using machine learning techniques developed at the AI for Health Institute at Washington University in St. Louis, Chenyang Lu, the Fullgraf Professor in the university's McKelvey School of Engineering, collaborated with Jacob Greenberg, MD, assistant professor of neurosurgery at the School of Medicine, to develop a way to predict recovery more accurately from lumbar spine surgery.
This non-invasive real-time approach is more effective than conventional methods and could be adopted for clinical practice to improve the accuracy of diagnosis and workflow, pending testing on larger and more ethnically diverse numbers of patients, suggest the researchers.