• Johannes Vedder will present StudyU at the Heidelberg Spring Symposium on Medical Informatics on May 8! Here is the program.
• Congratulations, Juliana for your accepted talk at the upcoming 44th Annual Conference of the International Society for Clinical Biostatistics!
• Congratulations, Thomas for your accepted talks at the upcoming 44th Annual Conference of the International Society for Clinical Biostatistics and the Symposium of International Symposium on Forecasting!

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.

• Dr. Stefan Konigorski (Head of lab)
• Marco Piccininni, PhD (Postdoc)
• Dr. Rebecca Paprott (Postdoc)
• Juliana Schneider (PhD student)
• Thomas Gärtner (PhD student)
• Hannah Neumayer (Scientist)
• Jessica Skalmowski (Scientist)

• Johannes Vedder (Master student): Senior developer for StudyU
• Ibrahim Oezkan (Master student): Developer for StudyU
• Md Raju Ahmed (Master student): Developer for StudyU

• Godsway Sackey (Master thesis): Use StudyU in Ghana!
• Maliha Raihan Pranti (Master thesis): How to deal with missing data in N-of-1 trials?
• Dr. Valentin Vetter (Master thesis): Reduce stress in physicians with N-of-1 trials in StudyU
• Dominik Meier (Master thesis): Adaptive N-of-1 trials
• Sandro Steinwand (Master thesis): Diet N-of-1 trials
• Victoria Ayvasky (Master thesis): Risk prediction models for endometriosis
• Saif Al-Oraibi (Master thesis): Automated patient-centric reports of N-of-1 trials
• Mohammad Abralur Rahman Akash (Master thesis): N-of-1 trials of smartphone user behaviour

• Methodology for Innovative N-of-1 trials
• Causal inference in prediction models
• Software tools for personalized prevention and personalized medicine:
  • StudyU: Platform for designing designing, implementing, and conducting digital health interventions through N-of-1 trials
  • StudyMe: App that allows everyone in the general population to design and perform an N-of-1 trial to investigate the effectiveness of one or more health interventions on a health outcome that they are interested in.
• N-of-1 trials using StudyU in prevention and clinical care, studying the effect of different health interventions in different populations, for example:
  • open-label placebo to reduce antidepressant discontinuation symptoms
  • anti-stress interventions in physicians in training
  • non-pharmacological interventions to improve sleep
  • physician-patient-derived interventions in chronic pain
  • fasting interventions to mitigate side effects in breast cancer patients
  • and many more.
  • See the StudyU Designer for more details.
• MeMäF: Improving women's health with a digitally supported care model for girls and young women with menstrual pain

• Susan Murphy, Statistical Reinforcement Learning lab, Harvard University
• Chris Schmid & Jeff Huang, Brown University
• Jane Nikles, University of Queensland
• Parag Goyal, Weill Cornell Medicine
• Sungho Won, Health Statistics lab, Seoul National University
• Thomas Fuchs, Ipek Ensari, Robert Hirten, Matteo Danieletto, David Kimhy, Icahn School of Medicine at Mount Sinai

We are looking for interested Master students and HiWis to support our work on apps (StudyU, StudyMe) and our work on statistical & machine learning models for their analysis. See here for more details.

• Dr. Luca Meoli (Guest scientist, scientist at Charité Berlin)
• Mohammad Asaduzzaman Miah (Master student 2023-24)
• Max Kraftberger (Master student 2023-24)
• Halil Goecer (Master student 2023-24)
• Sascha Obst (Master student 2023)
• Alisher Turubayev (Master student 2023)
• Jannis Baum (Bachelor student 2023)
• Danielle Cohen (Master student 2022-23, now at Deloitte)
• Larissa Röhrig (Master student 2022-23, now at KBV)
• Alexander Zenner (Master student 2020-21, now at Google)
• Nils Strelow (Master student 2020-21, now at Google)
• Lukas Ehrig (Master student 2021-22)
• Francisco Rios (Research Associate 2021-22, now at LaGeSo)
• Lasse von der Heydt (Research Associate 2021-22, now at Univ of Oxford)
• Mohammad Wasil Saleem (Master student 2021)