The Health Intervention Analytics Lab is a junior research group headed by Dr. Stefan Konigorski, Senior Researcher in the chair of Digital Health & Machine Learning and Adjunct Assistant Professor at the Icahn School of Medicine at Mount Sinai in New York.
The group was founded in May 2021 and is pioneering work on methodology and open source tools to perform N-of-1 trials in order to investigate the effect of digital health interventions on an individual level. We have developed the StudyU platform and StudyMe app that allow researchers, physicians and citizens to easily design and conduct N-of-1 trials and find out if health interventions have an effect. The aim is to allow everyone to setup and conduct N-of-1 trials digitally and support open, reproducible science through the platform, based on novel developed methodology integrating causal inference, statistics, deep learning and reinforcement learning. Clinical studies in collaboration with clinicians are running worldwide using StudyU, encompassing preventive interventions with healthy students, as well as interventions in people with chronic pain, endometriosis, depression, and breast cancer. In addition to N-of-1 trials, the group is working on adaptive trials and micro-randomized trials in order to implement and analyze effects of adaptive health interventions.
As a second focus, we aim to help improving health prevention and healthcare by work on clinical risk prediction models and as evaluator in the MeMäF project.
