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X ray - pneumonia categorization

Three CV models to predict pneumonia in X-ray images trained on this repo on kaggle

Problem

In the light of current epidemic machine learning may come in handy to help radiologists, hence I decided to train a few models that would be a useful in this setting. I've set a goal of validation accuracy over 80%.

Data

As per of repository descirption: "The dataset is organized into 3 folders (train, test, val) and contains subfolders for each image category (Pneumonia/Normal). There are 5,863 X-Ray images (JPEG) and 2 categories (Pneumonia/Normal).

Chest X-ray images (anterior-posterior) were selected from retrospective cohorts of pediatric patients of one to five years old from Guangzhou Women and Children’s Medical Center, Guangzhou. All chest X-ray imaging was performed as part of patients’ routine clinical care. "

Models tested

CNN

CNN-1

Efficenet

EFF-1

Mobilenet

Mobile_1

Model chosen

As per chosen target - only the CNN has met over >80% validation accuracy, thus being the only project being ported to the ruidmentary implementation in "X_ray_implement.ipynb" via Keras' serialization.

About

Three CV models to predict pneumonia trained on this <a href = "https://www.kaggle.com/datasets/paultimothymooney/chest-xray-pneumonia">repo </a> on kaggle

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