It is a working Deep Learning model that can be used to predict whether a patient is infected with Malaria or not. It uses Deep Convolutional Neural Network on training sample of about 220 images each of infected as well as non-infected human blood cells.
Malaria is a life-threatening disease caused by parasites that are transmitted to people through the bites of infected female Anopheles mosquitoes.
It is preventable and curable.
In 2018, there were an estimated 228 million cases of malaria worldwide.
The estimated number of malaria deaths stood at 405 000 in 2018.
Children aged under 5 years are the most vulnerable group affected by malaria;
in 2018, they accounted for 67% (272 000) of all malaria deaths worldwide.
The WHO African Region carries a disproportionately high share of the global malaria burden.
In 2018, the region was home to 93% of malaria cases and 94% of malaria deaths.
The modelling has been done by two methods :-
- Model from scratch
- Using Transfer Learning
The list of essential tools we require are :-
Create a new environment
conda create -p venv python==3.10 -y