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Malaria-Detection

Malaria must be recognized promptly in order to treat the patient in time. Delay in diagnosis and treatment could lead to the death of the malaria patient.

In this project , I used Convolutional Neural Network to classify the Malaria cell images into two categories

  • Parasitized (infected)
  • Uninfected

The dataset is taken from the Malaria Dataset from Kaggle.

The dataset has a total of 27558 images in which 17636 were used for training, 4410 for validation and 5512 for testing.

Confusion Matrix

mat

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This repository contains the code for the machine learning model which is used to detect whether a cell image is Parasitized or uninfected

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