AI & Machine Learning
Benchmarking Clinical NER
Score an OpenMed clinical or biomedical NER model against a user-supplied gold corpus with entity-level precision, recall, and F1, then break errors down per label. Use when the user wants a seqeval-style scorecard, strict vs partial (relaxed) span matching, a per-label confusion matrix, false-negative / false-positive examples, or to debug why a model misses entities. Trigger on \"evaluate NER\", \"entity-level F1\", \"seqeval\", \"precision recall F1\", \"confusion matrix\", \"error analysis\", \"strict vs partial match\", or \"score against gold\" in an OpenMed context. The gold corpus is user-supplied; OpenMed bundles no i2b2/n2c2/MIMIC data.
- Publisher / source
- maziyarpanahi/openmed (found on GitHub top repositories)
- Upstream record
- maziyarpanahi/openmed
- Version
- Version 1
- Published
- Publication review
- Approved for publication
- Content fingerprint
3b009e05549b315167fb41a54788bacc969545899fde98a7dd2a22944d6cc252