Healthcare Analytics

Over the course of the past decade the ability to translate data into insights has quickly become a highly in-demand skill by all. The projects mainly aims at extracting useful insights from the health care domain using Machine learning through Python programming. It provides tools to enable analytics in the medical domain for ailments that are a frequent norm of this generation.

Below are the projects that we have executed:

1. Framingham case study

The Framingham Heart Study (FHS) is dedicated to identifying common factors or characteristics that contribute to cardiovascular disease (CVD).

In this project, students will have a glimpse into how Framingham data can be used to help predict the future risk of a patient contracting cardiac disease through machine learning models.

Click here to go to Framingham case study.

2. Good Health case study

The Pima Indians long have intrigued researchers because they suffer from one of the highest rates of diabetes in the world. Studies have yet to pinpoint the reasons for the Pimas' poor health, but scientists suspect that it is a result both of genetic factors, which predispose the group to high rates of diabetes and obesity, and of environmental changes.

The objective of the dataset is to diagnostically predict whether or not a patient has diabetes, based on certain diagnostic measurements included in the dataset.

Click here to go to Good Health case study

3. Study on Hepatitis

In this project, students will have a glimpse into how hepatitis data can be used to help understand survival statistics of those who contract hepatitis.

Click here to go to Hepatitis case study.