“We are working to systematically devise ways of developing and implementing innovative new tools in clinical practice,” explained Prof. Friedman. “Around 10 years ago, we started analysing physiological signals in an attempt to determine disease at an earlier stage than was then possible. We have made some remarkable findings, which keep bringing us back to the obvious question, ‘Can we do something to identify disease before it becomes manifest?’”1,2
Prof. Friedman’s Paul Hugenholtz Lecture looks at the growing role of artificial intelligence (AI) in medicine. “The key,” he said, “is to take complex physiological signals and apply machine learning to transform standard, widely available tests into tools that identify occult or impending disease before illness and disability strike.” He calls this type of investigation ‘deep phenotyping.’ “Historically, clinical phenotype was determined by physical examination. Then came an ECG, then X-ray, and then more sophisticated imaging. Each of these tools provided a more sensitive way to look at what is happening within the body. In this latest advance, we are able to take electrical signals and process them in different ways so that we can characterise what makes one individual different from another; why one becomes ill, why one is at risk of becoming ill and why yet another is healthy,” said Prof. Friedman.
AI is going to be essential to the future of medicine. “As populations get older, we have more and more people with cardiovascular disease. We have to learn to balance improved care with limited healthcare resources. Using widely available tools to identify disease early and prevent its progression is going to bring enormous benefits to patients and also to healthcare workers, who are struggling to meet the demands of the system,” Prof. Friedman suggested, continuing, “The power of AI is such that a clinician does not have to be an expert in a particular therapeutic area, but he or she will be able to share information with more expert clinicians, when needed.”
Moving forward, Prof. Friedman thinks that medical AI will become a part of our everyday lives. “Many of us are already using health devices and the line between consumer and medical tools has become blurred. My feeling is that we are going to get even more creative at embedding these devices into the fabric of our lives to help improve the health of our societies.”