Pathogen Prediction Using Neural Networks Trained On Chest X-Ray Images

Jon Ambler, Ayush Garg, Sylvia Lee, Ishaan Narang and Volunteers

Introduction:

Pathogens, affecting the respiratory system, often impact lungs of a person. Comparing the radiograph of the affected person with that of a normal person reveals traces that can help in identification of the pathogen in question, and thus makes the treatment process more streamlined.

Scope:

In this project we seek out to train a neural network on chest radiograph images. The training will be done using Google’s auto vision ML which automatically determines the best model to use depending on the dataset provided. This model will be connected to a front-end application which will be built using flask.

Requirements:

We welcome individuals who are adept in one or more of the following skills:

• Python
• OpenCV, Tensor flow and Keras
• Html, CSS and JavaScript for the front end
• Data Collection
• Radiograph analysis
• Flask
• Google Cloud Platform

Our utmost priority will be to come up with a finely curated dataset and a user-friendly frontend which will make the project readily accessible for the public domain.

To help contribute and join the project please email at ayush@science.org.in

Author: Ayush Garg

Student at GIIS Singapore having great interest in artificial intelligence and machine learning. Co Founder of science.org.in. Interested in solving real world problems using ML.