New AI model learns from thousands of possibilities to suggest medical diagnoses and tests

AI has, for some time, been applied to diagnose medical conditions in specific fields. It can build on knowledge of particular disciplines to hone in on details such as the shape of a tumor that suggests breast cancer or abnormal cells that indicate cervical cancer. While AI is very good when trained on years of human data in specific domains, it has not been able to deal with the huge number of diagnostic tests (about 5000) and disorders (about 14,000) of modern clinical practice. Now, a new algorithm developed by engineers at the USC Viterbi School of Engineering can think and learn just like a doctor but with essentially infinite experience. The work comes out of the lab of Gerald Loeb, a professor of biomedical engineering, pharmacy and neurology at USC Viterbi School of Engineering and a trained physician. Loeb spent years applying AI algorithms to haptics and building robots to sense and identify materials and objects.