Translational Science - Prof. Jörg Goldhahn

Open Opportunities

Modeling Contextual Data to Reduce Outcome Variation: Analysis of the StudentLife Dataset ETH Zurich Translational Science - Prof. Jörg Goldhahn This project aims to systematically explore how "context" can be conceptualized and used to model outcomes in clinical research. This project focuses on analyzing the StudentLife dataset to explore how capturing contextual data can reduce variation in key outcome measures, such as the PHQ-9 (a measure of depression). The project aims to model how contextual covariates can explain variation over time, particularly during periods of increasing stress, such as a college semester. The findings will contribute to a viewpoint paper and a detailed analysis of the impact of contextual data on reducing trial sizes in research. Health Information Systems (incl. Surveillance) Master Thesis

Systematic Literature Review and Ontology Development for Contextual Information in Concept Models ETH Zurich Translational Science - Prof. Jörg Goldhahn This project aims to systematically explore how "context" is conceptualized and represented within conceptual models across various Therapeutic Areas (TAs) in clinical research. The goal is to review existing literature, analyze qualitative research, and identify common themes and differences in how context, environment, and adaptation are integrated into these models. The project will result in a comprehensive review paper, the development of an initial ontology, and a gap analysis of existing datasets and sensors used to capture contextual information. Health Information Systems (incl. Surveillance) ETH Zurich (ETHZ), Master Thesis