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+Bio-Epidemiology-NER is an Python library built on top of biomedical-ner-all model to recognize bio-medical entities from a corpus or a medical report
+
+[![Downloads](https://static.pepy.tech/personalized-badge/bio-epidemiology-ner?period=total&units=international_system&left_color=black&right_color=green&left_text=Downloads)](https://pepy.tech/project/bio-epidemiology-ner)
+<a href="https://pypi.org/project/Bio-Epidemiology-NER/">
+    <img alt="CI" src="https://img.shields.io/badge/pypi-v0.1.3-orange">
+</a>
+<a href="https://youtu.be/rYJOpUVWszY">
+    <img alt="CI" src="https://img.shields.io/badge/Demo-Video-red">
+</a>
+<a href="https://journals.plos.org/digitalhealth/article?id=10.1371/journal.pdig.0000152">
+    <img alt="CI" src="https://img.shields.io/badge/Research-Paper-green">
+</a>
+
+| Feature  | Output  |
+|---|---|
+| Named Entity Recognition | Recognize 84 bio-medical entities |
+| PDF Input | Read Pdf and tabulate the entities|
+| PDF Annotation | Annotate Entities in a medical pdf report|
+
+## Tutorial
+[<img src="https://github.com/dreji18/Bio-Epidemiology-NER/blob/main/output/thumbnail.png" width="50%">](https://youtu.be/xpiDPdBpS18 "Watch the video")
+
+## Installation
+
+Use the package manager [pip](https://pip.pypa.io/en/stable/) to install Bio-Epidemiology-NER
+
+```bash
+pip install Bio-Epidemiology-NER
+```
+
+This package has dependency over Pytorch, please install the required configuration from this link https://pytorch.org/get-started/locally/
+
+## Usage
+
+## NER with Bio-Epidemiology-NER
+```python
+# load all the functions
+from Bio_Epidemiology_NER.bio_recognizer import ner_prediction
+
+# returns the predicted class along with the probability of the actual EnvBert model
+doc = """
+	CASE: A 28-year-old previously healthy man presented with a 6-week history of palpitations. 
+      The symptoms occurred during rest, 2–3 times per week, lasted up to 30 minutes at a time 
+      and were associated with dyspnea. Except for a grade 2/6 holosystolic tricuspid regurgitation 
+      murmur (best heard at the left sternal border with inspiratory accentuation), physical 
+      examination yielded unremarkable findings.
+      """
+
+# returns a dataframe output
+ner_prediction(corpus=doc, compute='cpu') #pass compute='gpu' if using gpu
+
+```
+
+## Annotate the entities in a Medical Report and export as pdf/csv format 
+```python
+# load all the functions
+from Bio_Epidemiology_NER.bio_recognizer import pdf_annotate
+
+# enter pdf file name
+pdffile = 'Alhashash-2020-Emergency surgical management.pdf'
+
+# returns a annotated pdf file
+pdf_annotate(pdffile,compute='cpu', output_format='pdf') #pass compute='gpu' if using gpu
+
+# returns a csv file with entities
+pdf_annotate(pdffile,compute='cpu', output_format='csv') #pass compute='gpu' if using gpu
+
+# return both annotated pdf and csv file
+pdf_annotate(pdffile,compute='cpu', output_format='all') #pass compute='gpu' if using gpu
+
+```
+
+
+## About the Model
+The model within this package is an English Named Entity Recognition model, trained on Maccrobat to recognize the bio-medical entities (84 entities) from a given text corpus (case reports etc.). This model was built on top of distilbert-base-uncased
+
+- Dataset : Maccrobat https://figshare.com/articles/dataset/MACCROBAT2018/9764942
+- Carbon emission : 0.0279399890043426 Kg
+- Training time : 30.16527 minute
+- GPU used : 1 x GeForce RTX 3060 Laptop GPU
+
+for more details regarding the entities supported, check the config file https://huggingface.co/d4data/biomedical-ner-all/blob/main/config.json
+
+## Ownership & License
+This Package is part of the Research topic "AI in Biomedical field" conducted by Deepak John Reji, Shaina Raza. If you use this work (code, model or dataset),
+
+Please cite our [**Research Paper**](https://github.com/dreji18/Bio-Epidemiology-NER/blob/main/CITATION.cff) 
+
+and star at: https://github.com/dreji18/biomedicalNER
+
+[MIT](https://choosealicense.com/licenses/mit/) License
+
+## You can support me :)
+
+<a href="https://www.buymeacoffee.com/deepakjohnreji" target="_blank"><img src="https://cdn.buymeacoffee.com/buttons/v2/default-yellow.png" alt="Buy Me A Coffee" style="height: 60px !important;width: 217px !important;" ></a>
+