The malaria is a disease that is spread by a bite of an infected female mosquito. The malaria is caused by the Plasmodium which is a genus of parasites. We know five types of Plasmodium that can infect humans. The malaria is a global concern, every 2 minutes, a child dies of malaria. And each year, more than 200 million new cases of the disease are reported, mostly in Africa. The early diagnosis could help treat and control the disease.
Once the human get infected by the malaria, the Plasmodium parasite begin to spread and appears in the host’s blood. By detecting this Plasmodium through a blood smear test and the ”thick drop” method, it is possible to know whether a human has contracted the malaria.
In this challenge you will have access to pre-processed images of segmented cells from the thin blood smear slide. Your goal is to detect parasitized cell images from uninfected ones in order to diagnose malaria.
Brought to you by the Medichal team (firstname.lastname@example.org)
Data were provided by NIH
The problem is a binary classification problem. Each sample is an an image of a cell which can be infected or not.
You are given for training a set of images which is reduced to 19 numerical features, so you have
a matrix containing those 19 features for 60% of the total number of images in a matrix called X_train.
For the labels, you have an array of labels of same length as the matrix filled with zeros and ones which indicates whether the cell is infected or not.
Your task is to train a model which predicts the labels of the test sample matrix X_test and the validation sample matrix X_valid.
There are 2 phases:
This sample competition allows you to submit either:
The submissions are evaluated using the area under the roc curve metric.
Submissions must be made before the end of phase 1. You may submit 5 submissions every day and 100 in total.
This challenge is governed by the general ChaLearn contest rules.
Start: Nov. 15, 2018, midnight
Description: Development phase: tune your models and submit prediction results, trained model, or untrained model.
Start: April 30, 2050, midnight
Description: Final phase (no submission, your last submission from the previous phase is automatically forwarded).
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