iajaykarthick/NER-medical-text

This project is to develop a named entity recognition (NER) model to identity medical entities such as diseases, symptoms, treatments in the unstructured medical text written in natural language.

27
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Experimental

Automatically scans and extracts key medical information like diseases, symptoms, and treatments from free-form medical notes, research papers, or patient records. It takes raw, unstructured medical text as input and identifies and categorizes these important entities. This helps medical researchers, clinicians, and data analysts quickly find specific information in large volumes of text.

No commits in the last 6 months.

Use this if you need to rapidly identify and categorize specific medical entities from large amounts of unstructured text data, such as clinical notes or scientific literature.

Not ideal if your medical text is already highly structured or if you only need to extract very simple, predefined keywords.

medical-information-extraction clinical-data-analysis biomedical-research healthcare-analytics patient-record-processing
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 8 / 25
Community 14 / 25

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Last pushed

Oct 15, 2024

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