Machine learning makes its mark on medical imaging and therapy – Physics World

Artificial intelligence has potential to improve the operation of many essential tasks in various fields of medicine and biomedicine – from dealing with the massive amount of data generated by medical imaging, to understanding the evolution of cancer in the body, to helping design and optimize patient treatments. At last week's APS March Meeting, a dedicated focus session examined some of the latest medical applications of artificial intelligence and machine learning. Opening the session, Alison Deatsch from the University of Wisconsin, Madison, discussed the use of deep learning for diagnosing and monitoring brain disease. "Brain disorders and neurodegenerative disease are some of the most costly diseases, both in terms of human suffering and economic costs," she explained. The reason is that most of these conditions – which include Alzheimer's and Parkinson's disease, autism spectrum disorder and mild cognitive impairment (MCI), among others – lack reliable tools for diagnosis and progression monitoring and, as such, are often misdiagnosed.