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Eshaan is a first year Computer Science student from R. V College of Engineering, Bangalore, India. His hobbies include playing sports like chess and table tennis and his major interests include learning various concepts of machine learning. Although a beginner in the field, having done concepts from preprocessing to performing machine learning like regression, classification and clustering on tabular data, he still aims to learn more concepts like Neural Networks and Natural Language Processing. HPCC Systems has provided him with a keen interest in learning various concepts of M.L in a conceptual manner.

Poster Abstract

Introduction:

Medical Infrastructure is now an important parameter as we look at the advancement of countries on the front of possessing a strong research and development environment as well as increasing well-being of its citizens. It can be safe to say that a country with a good medical infrastructure can attract a higher skilled crowd and a more urbanized crowd. It can be used as an overall development indicator of a nation. 

Objective:

Our prime objective in the project is to obtain data on important parameters which are related to the health affairs of various country and perform various statistical operations on it using HPCC Systems as well as making use of visualization tools to analyze the data more easily. Making use of all these operations will give us an idea as to how a scattered data that can undergo all these operations, can give us an understanding regarding usage of 
statistics in real life applications and also help us analyze where various countries stand in terms of medical infrastructure. 

Methodology:

The ideas in the project can be achieved by making use of the ECL IDE and transferring all the collected data like data on hospital beds, medical staff, vaccination drives and more data onto the cluster. We make use of the inbuilt functions to bring all the data together and bring it in a uniform format along with the usage of mathematical operations like covariance and correlation to understand relations among the parameters. We can make use of regression models and find relations between the data parameters, which have numerous Machine Learning applications along with the usage of the Visualization bundle, to display a pictorial and easier visual representation of big data

Presentation

In this Video Recording, Eshaan provides a tour and explanation of his poster content.

Analysis of Country-wide Healthcare Data and Selection of an Ideal Machine Learning Model for Prediction of GHSI

Click on the poster for a larger image.

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