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Pneumonia Prediction Using chest x-ray Image Machine Learning

Posted on June 30, 2021January 21, 2024 by Yugesh Verma

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Chest x-ray: An x-ray exam will allow your doctor to see your lungs, heart and blood vessels to help determine if you have pneumonia. When interpreting the x-ray, the radiologist will look for white spots in the lungs (called infiltrates) that identify an infection. Build an algorithm to automatically identify whether a patient is suffering from pneumonia or not by looking at chest X-ray images. The algorithm had to be extremely accurate because lives of people is at stake. This is a Flask web app designed to analyze a chest x-ray and predict whether a person has TB/pneumonia or not.

Models :

The model is based on a convolutional neural network that has been trained on a dataset of 800 images from two sources

The model has an overall accuracy of 83% and an F1 score of 80%.

A negative prediction means that the chest X-ray is most likely normal while the contrary is implied by a positive prediction

Environment and tools

Runtime Python Version : python-3.8.2

Datasets Link

The dataset can be downloaded from the kaggle website which can be found here.

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