arXiv (All)
open access
Detecting adverse high-order drug combinations from individual case safety reports using computational statistics on disproportionality measures
Adverse drug reactions linked to the intake of drug combinations are a critical concern in pharmacovigilance, particularly as the controlled environment of clinical trials often lacks the scale and diversity to detect rare events involving multiple medications. While spontaneous reporting systems pr
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
- Detecting adverse high-order drug combinations from individual case safety reports using computational statistics on disproportionality measures#1425719
- Evaluating ActionADE in Reducing Adverse Drug Reactions#883572
- From bedside observations to clinical decision support system (CDSS) rules: using real-world adverse drug events (ADEs) data to identify high-risk iatrogenic situations#304636
- Factors contributing to medication safety incidents observed by community pharmacists - a content analysis of incident reports.#1204659
- Development and analysis of a SmPC-based machine-readable dataset of contraindications for clinical decision support and real-world data analysis#1071815
Record · ID 1423697
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