Swiss FIRE Database
Cross-source consensus on Swiss FIRE Database from 1 sources and 5 claims.
1 sources · 5 claims
Preparation
Risks & contraindications
Where it comes from
Highlighted claims
- The real-world target trial emulation used the Swiss FIRE primary-care database. — Joint Treatment Effect Estimation from Incomplete Healthcare Data: Temporal Causal Normalizing Flows with LLM-driven Evolutionary MNAR Imputation
- Imputation was tested on a semi-synthetic FIRE EHR-based dataset with ten synthetic longitudinal biomarkers. — Joint Treatment Effect Estimation from Incomplete Healthcare Data: Temporal Causal Normalizing Flows with LLM-driven Evolutionary MNAR Imputation
- Privacy restrictions prevent public release of the FIRE data. — Joint Treatment Effect Estimation from Incomplete Healthcare Data: Temporal Causal Normalizing Flows with LLM-driven Evolutionary MNAR Imputation
- Eligible FIRE cohort adults had type 2 diabetes before or at entry and at least one weight measurement in the prior 365 days. — Joint Treatment Effect Estimation from Incomplete Healthcare Data: Temporal Causal Normalizing Flows with LLM-driven Evolutionary MNAR Imputation
- FIRE cohort exclusions included prior comparator drug class, type 1 diabetes, and eGFR of 30 or lower. — Joint Treatment Effect Estimation from Incomplete Healthcare Data: Temporal Causal Normalizing Flows with LLM-driven Evolutionary MNAR Imputation