Bielefeld Pub
metadata only
Validating methods for inferring co-occurring diseases: a flexible framework for simulating synthetic data
Marchi H, Schmiegel S, Schamberger T, Fuchs C. Validating methods for inferring co-occurring diseases: a flexible framework for simulating synthetic data. BMC Medical Research Methodology . 2026;26(1): 184.
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Code and data for: Composable probabilistic models can lower barriers to rigorous infectious disease modelling#231915
- An integrated evaluation framework for synthetic clinical data in severely imbalanced settings: fidelity, privacy-risk profiling, and diagnostic utility.#685868
- From Data Lifting to Continuous Risk Estimation: A Process-Aware Pipeline for Predictive Monitoring of Clinical Pathways#155286
- contactsurveys: Download Contact Surveys for Use in Infectious Disease Modelling#452317
- French COVID Cohort#1031234
Record · ID 965547
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive