Stanford Seminar - A Billion Medical Devices - Using far from perfect ML to help patients

February 14, 2025 Mayank Goel, Carnegie Mellon University As we live longer, we are also living with more diseases. The need to identify illness symptoms and manage them has been increasing rapidly. Our personal devices have a role to play in helping us take care of ourselves outside a doctor's clinic or hospital. Technology's role in healthcare is already quite ubiquitous in the form of step counters and heart rate monitors. However, we can go far beyond these coarse measures. I will provide an overview of our efforts at building real-time machine-learning systems that measure depression symptoms, fatigue, sleep quality, and hyperactivity. While useful, these machine learning systems will probably never be perfectly accurate. The sensed information will always be noisy. Moreover, the user won't know how to interpret and use measured information. I will present our ideas on how to make the inferred information actionable to the patients, caretakers, and doctors. I will also talk about the role of noisy machine learning systems and how a user can counter the system's inherent error and uncertainty. Ultimately, we aim to build systems that help us manage our health without requiring perfectly accurate inferences. About the speaker: Mayank Goel is an Associate Professor in S3D and HCII in the School of Computer Science at Carnegie Mellon University. His research focuses on designing new sensing systems using sensors and devices already present in the environment. He ultimately solves complex problems in various domains, including health sensing, technologies for global development, and novel interactive systems. His inventions are part of consumer products built by companies such as Apple, Google, and Meta. Some of his work is currently deployed in clinics worldwide and is used by several thousand patients every month. Many of these technologies are presently going through regulatory approvals. More about the course can be found here: https://hci.stanford.edu/semin