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 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. First clinical studies in collaboration with clinicians are running using StudyU. 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.
The software tools and clinical studies provide empirical clinical data for our methodological work on statistical and machine learning methods to analyze the resulting complex time series data. We employ methods from causal inference by viewing the data embedded in its causal structure. Further analytic methods of interest encompass clinical risk prediction models.