SuperBruceJia/MedicalNER
An implementation of several models (BiLSTM-CRF, BiLSTM-CNN, BiLSTM-BiLSTM) for Medical Named Entity Recognition (NER)
This project helps medical and clinical healthcare professionals automatically identify and extract key pieces of information, like disease names or drug dosages, from medical text. You input raw medical text, such as clinical notes or research papers, and it outputs the same text with specific medical entities tagged and categorized. This tool is designed for data scientists or researchers working with large volumes of medical documentation.
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Use this if you need to automatically extract specific medical terms and concepts from clinical notes, research papers, or other medical text.
Not ideal if you need to process medical texts that contain very rare entities (fewer than 500 samples) or if you require GPU acceleration for processing speed.
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19
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2
Language
Jupyter Notebook
License
MIT
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Last pushed
Dec 22, 2024
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