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Medical Ner Roberta

Developed by nairaxo
A medical domain named entity recognition model based on the RoBERTa architecture, used to identify specific entities from medical texts
Downloads 58
Release Time : 11/17/2024

Model Overview

This model is a named entity recognition (NER) model trained on medical domain texts, based on the RoBERTa architecture, capable of identifying medical-related named entities.

Model Features

High-precision Medical Entity Recognition
Achieved 93.06% precision and 94.31% recall on the evaluation set
Optimized Training Process
Trained for 20 epochs using cosine learning rate scheduler and adamw_torch optimizer
Medical Domain Specialization
Named entity recognition capability specifically optimized for medical texts

Model Capabilities

Medical Text Analysis
Named Entity Recognition
Entity Classification

Use Cases

Medical Information Processing
Electronic Medical Record Analysis
Extract key medical entities such as diseases, medications, symptoms, etc. from electronic medical records
High-accuracy identification of medical-related entities
Medical Literature Processing
Automatically annotate professional terms and entities in medical research literature
Improve efficiency in medical literature processing
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