This tool converts Lifelines cohort study data from CSV to CDF/JSON, a format used in the MyDigiTwin project. Lifelines tracks health data over time, but variables are often scattered across files, making analysis difficult. CDF organizes data per participant, enabling FHIR/MedMij-compliant analysis
Cohort studies play a crucial role in understanding the relationships between various factors and health outcomes over time. These studies collect extensive data from participants, including demographic information, clinical variables, lifestyle factors, and biomarkers. However, analyzing cohort study data often poses challenges, particularly when assessing variables across different time points. The data for the same variable is typically scattered across multiple files, each representing a specific assessment or follow-up visit. This fragmentation makes it difficult to perform comprehensive longitudinal analyses, or in the particular case of the MyDigiTwin project, to compute multiple points in time of the same variable to map it to standards like FHIR/MedMij. This tool transforms data from the Lifelines cohort study in CSV (Comma-Separated Values) format into a format we called CDF/JSON (Cohort Data Format), which is already used by other data analysis tools in the MyDigiTwin project. A CDF format describes all the variables, and their values over time (i.e., each assessment), of an individual study participant. This format is particularly useful for the generation of FHIR/MedMij-compliant data (one of the aforementioned analysis tools).