Data Science as a Service

Data is valuable raw material. It needs mining, careful processing, and polishing.
We assist you in research and development by sample size estimation, planning and conducting statistical evaluation, data visualizations, and exploratory data mining.

For your data management, we provide electronic case report forms (eCRFs) and assist you in digitizing information hidden in all sorts of documents.
Understanding statistical results or conducting analyses in-house requires competences. We provide customized seminars on statistical analyses as well as introductory classes in the use of R, a standard tool in scientific data analytics.

Thinking with data unveils the value in your data!



February 2024 || HealthTwiSt analyzed data from a pilot study with 62 adolescent patients with anorexia nervosa. Results demonstrated that for 2/3rd of patients eligible for a long hospitalization in the German health care system, outpatient, Family-based treatment (FBT) was a safe and feasible treatment alternative. Over 12 months, FBT lead to similar weight gain and reduction in eating disorder cognitions as inpatient treatment with fewer hospital days. This pilot study needs to be followed up by a larger, multicenter trial. The study was published in the International Journal of Eating Disorders: Comparing family-based treatment with inpatient treatment in youth with anorexia nervosa eligible for hospitalization: A 12-month feasibility study: Verena Haas, Katja Wechsung , Vivien Kaiser, Janine Schmidt, Klemens Raile, Andreas Busjahn, Daniel Le Grange, Christoph U Correll (full text).

Study on mitochondrial function

May 2023 || HealthTwiSt was involved in a clinical trial on biomarkers in mitochondrial diseases. Results have been published in Clinical and Translational Science: Identification of peripheral vascular function measures and circulating biomarkers of mitochondrial function in patients with mitochondrial disease: Sebastiaan J. W. van Kraaij, Diana R. Pereira, Bastiaan Smal, Luciana Summo, Anne Konkel, Janine Lossie, Andreas Busjahn, Tom N. Grammatopoulos, Erica Klaassen, Robert Fischer, Wolf-Hagen Schunck, Pim Gal, Matthijs Moerland (full text).


MAY 2023 || Due to the increasing importance and use of machine learning in research, we extended our seminar portfolio by a 2-week introduction to ML in R. Focus is on explainable ML to further the understanding of mechanisms underlying methods of the current AI developments. Methods covered include k nearest neighbors, regression trees, XGBoost, neural networks, PCA, LDA.