andreped/adverse-events

IEEE BIBM 2021: Bayesian optimization-guided topic modeling for automatic detection of sepsis-related events from free text

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Emerging

This tool helps medical professionals, researchers, or data analysts automatically identify sepsis-related events from large volumes of unstructured clinical notes. You input raw, free-text adverse event reports, and it outputs analyzed data that highlights potential sepsis cases, helping to streamline medical review and research. It's designed for anyone needing to efficiently process patient data for critical event detection.

No commits in the last 6 months.

Use this if you need to quickly and automatically identify mentions of sepsis in free-text clinical adverse event reports, saving significant manual review time.

Not ideal if your primary goal is to analyze structured patient data or if you need a pre-built, production-ready system for real-time clinical alerting.

clinical-text-analysis adverse-event-monitoring sepsis-detection medical-research healthcare-data-analysis
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 4 / 25
Maturity 16 / 25
Community 14 / 25

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Stars

7

Forks

3

Language

Python

License

MIT

Last pushed

Apr 16, 2023

Commits (30d)

0

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