- Data-efficient machine learning methods in the ME-TIME study: Rationale and design of a longitudinal study to detect atrial fibrillation and heart failure from wearables
- Causal inference using observational intensive care unit data: a scoping review and recommendations for future practice
- Integration of metabolomics with genomics: Metabolic gene prioritization using metabolomics data and genomic variant (CADD) scores
- Development and validation of an early warning model for hospitalized COVID-19 patients: a multi-center retrospective cohort study
- Dynamic Digital Twin: Diagnosis, Treatment, Prediction, and Prevention of Disease During the Life Course
- Single-cell immune profiling reveals thymus-seeding populations, T cell commitment, and multilineage development in the human thymus
- MiMIR: R-shiny application to infer risk factors and endpoints from Nightingale Health's 1H-NMR metabolomics data
- Metabolomic predictors of phenotypic traits can replace and complement measured clinical variables in population-scale expression profiling studies