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Clinicalnerpt Disease

Developed by pucpr
A BioBERTpt-based Portuguese clinical disease named entity recognition model, specifically designed to identify disease-related entities from Brazilian clinical texts
Downloads 23
Release Time : 3/2/2022

Model Overview

This model is part of the BioBERTpt project, specifically targeting disease entity recognition in Portuguese clinical texts, supporting clinical entity annotation compatible with UMLS

Model Features

Domain-Specific Pretraining
Domain-adapted training based on clinical narratives and biomedical papers
Multi-Entity Recognition
Can identify 13 types of clinical entities compatible with UMLS
Transfer Learning Optimization
Reduces the need for labeled data through transfer learning, improving performance for low-resource languages

Model Capabilities

Clinical Text Analysis
Disease Entity Recognition
Medical Concept Extraction

Use Cases

Clinical Record Processing
Electronic Medical Record Analysis
Automatically extracts disease diagnosis information from patient electronic medical records
F1 score improved by 2.72% compared to baseline models
Clinical Research Data Mining
Extracts disease-related entities from clinical research literature
Outperformed baseline models in 11 out of 13 evaluated entities
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