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Deep learning CNN model for pharyngitis (sore-throat) detection from images taken by smartphones

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Pharyngitis detection using deep learning CNN

Pharyngitis, commonly known as a sore throat, is a prevalent inflammatory condition affecting the throat. Detecting and diagnosing such common infections and diseases efficiently is crucial for timely treatment. In this repository, we explore the application of artificial intelligence techniques, specifically deep learning, to identify pharyngitis cases from images taken by smartphones.

The dataset used in training this model is a public dataset obtained from Toward automated severe pharyngitis detection with smartphone camera using deep learning networks

set-up

pip install -r requirements.txt

download the model

you can download the model manually from the release assets

or use the bash script

bash download_model.bash

Training

python train.py

Inference

python infer.py -i <path_to_image>

Acknowledgement

The Dataset

Toward automated severe pharyngitis detection with smartphone camera using deep learning networks

Yoo, TaeKeun (2020), “Toward automated severe pharyngitis detection with smartphone camera using deep learning networks”, Mendeley Data, V2, doi: 10.17632/8ynyhnj2kz.2

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Deep learning CNN model for pharyngitis (sore-throat) detection from images taken by smartphones

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