Health Data Science special interest group
The SIG Health data science is one of the special interest groups linked to the Data Science Research Programme and SAILs, the university wide AI programme. Group leaders are Wessel Kraaij and Marco Spruit.
- Wessel Kraaij
Health research, medical practice and consequently the whole population is increasingly affected by digitization, data science and AI. The possibilities for improving health outcomes on the individual, group and population level are vast, since more data becomes available and is increasingly being combined for improved risk detection, diagnosis, treatment and etiological research. Our group is concerned with analysing structured and unstructured data sources (real world data, routine care data, environmental data) for extracting new knowledge or prediction of health outcomes, by e.g. designing digital biomarkers and update /calibrate published models (the evidence base).
The group organizes monthly meetings (currently virtual) with a speaker or reading group. Membership is open for researchers from all faculties, but the group's focus is on method development for data science challenges in the health science domain.
15-4 2021, 16:00: webinar Saskia Koldijk UMCU : Study with Empatica wearables
Detecting physiological arousal in children using a wearable (Saskia Koldijk, UMC Utrecht, PsyData)
Aggression is one of the main causes of psychiatric admission, and manifests itself in different disorders. Coping with aggression is of importance for children themselves, as well as for staff. We aim to deploy wearables in clinical practice to support emotion regulation. In our research we asked 25 children from the psychiatry ward to wear an Empatica wearable for 5 days. Observations of behavior, especially aggressive incidents were made. Currently we are analyzing the relation between measured physiology over time and observed aggression. We consider to use multilevel modeling, but are also interested in discussing alternative analysis approaches with the SIG members.