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Medical NER
M
Medical NER
Developed by blaze999
A DeBERTa-based fine-tuned medical named entity recognition model capable of identifying 41 types of medical entities.
Downloads 14.76k
Release Time : 2/9/2024
Model Overview
This model is a fine-tuned version for medical named entity recognition (NER) tasks, based on the BERT architecture, suitable for extracting key medical entities from healthcare texts.
Model Features
Medical Entity Recognition
Accurately identifies 41 different medical entities, suitable for medical text analysis.
Efficient Fine-tuning
Efficiently fine-tuned based on the DeBERTa architecture, optimizing performance for medical named entity recognition.
Multi-task Support
Supports various medical text processing tasks, including diagnostic records, pathology reports, etc.
Model Capabilities
Medical Named Entity Recognition
Medical Text Analysis
Entity Classification
Use Cases
Medical Diagnosis
Diagnostic Record Analysis
Extracts key medical entities such as diseases and symptoms from patient diagnostic records.
Accurately identifies disease entities like CAD.
Pathology Report Analysis
Analyzes pathology reports to identify critical information such as cancer cell spread.
Identifies key information like cancer cell spread to pelvic lymph nodes.
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