An introduction to the field of Computational Psychiatry from the perspective of computer science, as informed by clinical practice.
(units 2-2-8) Thursdays, Rm 4-145, 11am-1pm
An introduction to the field of Computational Psychiatry from the perspective of computer science, as informed by clinical practice.
(units 2-2-8) Thursdays, Rm 4-145, 11am-1pm
Mental illness is a leading cause of disability worldwide, affecting both developed and developing countries. Mental health is an integral part of our overall health, yet in the U.S. only half of the people with mental illness ever seek treatment or get diagnosed; and among those who seek treatment, only 10% find a treatment that is effective. Furthermore, due to a growing and aging population, there is an increasing shortage of mental health professionals. Developing countries such as India have an even greater shortage, with only 6000 psychiatrists for a population of 1.3 Billion people; and many countries in Africa have few mental health care providers at all. In order to provide sustainable mental health services in the future, we are exploring how technology (computer science/AI) may be used to enable more effective and scalable therapies.
Advances in sensors, computation and mobile phones now provide new ways to measure and predict certain aspects of our mental health and behavior. From the clinical perspective, such technology tools can enable early detection of mental illness, more quantitative personalized treatment plans, more effective crisis interventions, and better monitoring once treatment has begun. From the point of view of wellness, technology measurement tools also provide the ability to improve life coaching, peer support, and improve independence and self-agency.
The emerging field of Computational Psychiatry combines artificial intelligence algorithms with a variety of technologies that can be applied to mental health. These include: mobile phones, wearable sensors, chatbots, social robots, and virtual reality, among others. In this course, we examine the current needs in mental health practice and explore the design of diagnostic and therapeutic systems that make use of these digital tools, and also consider potential risks (e.g. privacy, ethical use, bias, security) that should be considered when building such systems.
This class is designed for students who are interested in learning more about the real-world clinical practice of psychology and psychiatry, and exploring ways that technology can be applied.
This course meets once per week for 2 hours. The first hour of each class consists of a clinical discussion to provide background and motivation, describing a specific aspect of psychology or psychiatry, current approaches to treatment, and current challenges in mental health practice. The second hour of each lecture will be devoted to relevant technologies being developed for assessment, monitoring, and intervention.
Coursework and Design Exercises: This class has no exams, but there will be significant weekly reading assignments, as well as a short ~2-page weekly written asignment based on the readings. Over the course of the semester, there are three separate design exercises in which students shall create and present concepts for addressing specific needs in mental health and wellness. These design projects shall be presented in the form of a poster, a physical mock-up, or a software demonstration, as part of an interactive class poster/demo session. (the exact format will depend on the number of students in the class).
Graduate credit: Students seeking graduate credit will be required to submit an additional 10-page position paper, with references, reviewing one of the topic areas covered in class.
Grading: Grading is based on the design exercises, weekly written assignments, and class participation.
Rich Fletcher: Dr. Fletcher is a research scientist at MIT and is also an assistant professor of Psychiatry at the University of Massachusetts Medical School. Dr. Fletcher directs the Mobile Technology Group at MIT D-Lab, and has been working on mental health technologies for over 10 years, including 2 patents in this area as well as over 15 patents in the area of wireless sensors. Dr. Fletcher earned 4 degrees from MIT (Physics, Electrical Engineering, Information Technology M.S. and PhD) and has founded four companies over the years, in the area of wireless sensors and mobile health. Dr. Fletcher has led technology development for several NIH-funded studies in the areas of mental health, drug addiction, and behavior medicine.
Karin Hodges Dr. Hodges is a Licensed Psychologist and clinical researcher who specializes in treating mental illness and fostering mental wellness in children. She practices in Concord, MA. Dr. Hodges received education and training from UCLA, Antioch University, New England (AUNE), Dartmouth Medical Center, and Franciscan Hospital for Children, and she has also trained and worked in various elementary and middle schools and mental health clinics throughout New England, including in Roxbury, MA; Dorchester, MA; Ashfield, MA; Brookline, MA; as well as in Keene, NH. Dr. Hodges has taught courses in psychology at AUNE, including Tests and Measurements; Interventions; and Group Interventions.
Michaela Ennis (Course Assistant) Ms. Ennis is currently a PhD student and research assistant with Prof Justin Baker at Harvard Mclean Hospital. Michaela has a background in machine learning and neuroscience with undergraduate degrees from MIT in Electrical Engineering and Computer Science as well as Brain and Cognitive Science.
Guest Lectures This course will feature several invited lectures by clinicians and scientists from Harvard Medical School, Mass General Hospital, MIT, and Mass College of Art.
We would like to thank the MIT J-WELL program for providing support to make this class possible.