Predict Covid-19 Using CT Scan of Patient | Machine Learning (Python)

 In this project I try to create a covid-19 Predictor which can Input an CT Scan Image and predict whether That CT Scan image is from a Covid-19 Patient or not. The model consists of three convolution blocks with a max pool layer in each of them. This model has not been tuned for high accuracy. 

For this project we are using optimizers.Adam optimizer and losses. SparseCategoricalCrossentropy loss function.
We are saving the model using model.save('folder_path')

What is Covid-19

Coronavirus disease 2019 (COVID-19) is defined as illness caused by a novel coronavirus now called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; formerly called 2019-nCoV), which was first identified amid an outbreak of respiratory illness cases in Wuhan City, Hubei Province, China.

Create Covid-19 Prediction Model :

The model consists of three convolution blocks with a max pool layer in each of them. There’s a fully connected layer with 128 units on top of it that is activated by a relu activation function. This model has not been tuned for high accuracy, the goal of this tutorial is to show a standard approach.

Source Code:

covid-19_ct_predictor.IPYNB

Download IPYNB • 2KB

covid-19_ct_traineer.IPYNB

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Dataset:

Images-processed.zip

Download ZIP • 132.70MB