GERNERMED and GERNERMED-pp

The second model is an improved successor to the first, using transfer learning to enhance performance on the same German medical NER task, making them sequential versions rather than tools designed to be used together.

GERNERMED
38
Emerging
GERNERMED-pp
27
Experimental
Maintenance 0/25
Adoption 6/25
Maturity 16/25
Community 16/25
Maintenance 0/25
Adoption 5/25
Maturity 8/25
Community 14/25
Stars: 18
Forks: 6
Downloads:
Commits (30d): 0
Language: Python
License: MIT
Stars: 9
Forks: 3
Downloads:
Commits (30d): 0
Language: Python
License:
Stale 6m No Package No Dependents
No License Stale 6m No Package No Dependents

About GERNERMED

frankkramer-lab/GERNERMED

GERNERMED is the first open neural NER model for medical entities designed for German data.

GERNERMED helps medical and pharmaceutical professionals automatically identify key information within German-language medical texts. It takes unstructured German clinical notes, scientific papers, or drug descriptions as input and extracts specific entities like drug names, dosages, frequencies, and durations. This tool is useful for researchers, pharmacists, and medical data analysts working with large volumes of German medical data.

medical-nlp pharmacovigilance clinical-research drug-information health-informatics

About GERNERMED-pp

frankkramer-lab/GERNERMED-pp

GERNERMED++ is a transfer-learning-based open neural NER model for medical entities designed for German data.

GERNERMED++ helps medical professionals, researchers, or data analysts to automatically identify and extract key medication details from German medical texts. You input German clinical notes, patient records, or research papers, and it outputs highlighted specific entities like drug names, dosages, frequencies, durations, and forms. This tool is for anyone needing to efficiently structure information from large volumes of German medical text.

medical-nlp pharmacovigilance clinical-data-extraction medical-research health-informatics

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