In-Person Workshop: Harnessing Technology and AI to Expand the Reach of Lifestyle Medicine in Diabetes and Endocrine Practice

Nearly 80% of the U.S. population has one or more chronic metabolic diseases. Scaling of lifestyle medicine interventions is needed to bend the curve of disease burden and the corresponding unsustainable healthcare costs. A variety of innovative technical strategies have value in meeting this demand. These include virtual one-on-one health coaching sessions, multidisciplinary virtual appointments, remote monitoring with wearable technologies, and a variety of apps that address one or more pillars of lifestyle medicine. Furthermore, artificial intelligence (AI) has exciting potential for application in lifestyle medicine practice. AI is a branch of computer science that focuses on the theory and development of computer systems and algorithms capable of performing tasks that typically require human intelligence. Some of the areas in endocrinology where we can use technology include diabetes management, weight management, and thyroid disorders. In the first hour of this three-hour workshop, we will discuss wearable technologies, focusing on continuous glucose monitors and new vital signs monitors for the management of diabetes. With the help of a case study, we will review some of the benefits of these technologies, for example, patient empowerment, and challenges, for example, unexpected device failure. In the second hour, we will discuss the use of telemedicine and remote patient monitoring in obesity management to improve patient engagement and will present some real-world outcomes from published clinical studies. We will also spotlight several web-based applications that can be used to create personalized diet, activity, stress, and sleep plans for the management of obesity. In the third hour, we will explore the current uses and the future of AI in diagnosing and classifying thyroid nodules. Thyroid nodules are a common clinical problem, and thyroid cancers are the most common endocrine cancer. In 2017 the FDA approved AI cloud-based learning using ultrasound and cytopathological data for the diagnosis and classification of thyroid nodules. We will end the session with a short meditation session using some simple mindfulness technological tools.