Heart Risk Predictive Analytical with IBM SPSS
Project Description
IBM SPSS is used to build predictive analytical for find heart risk. This project is build based patient data and IoT ECG simulator data. IoT ECG simulator will generating heart risk singles. IBM SPSS classification model C 5.0 decision tree model is used for building the prediction.
Responsibilities
- Creating the model for predictive analytics and find the right modeling tools for prediction with great accuracy percentage.
- Creating IoT-(Internet of Things) ECG Simulator in Internet of things foundation from Bluemix and the collected ECG data stored in Bluemix Cloudant.
- Connect Bluemix to SPSS for source data patient data as well as ECG data for developing prediction model. Using type node and partition node to set the target attribute.
- Getting the user input data and prediction result to build and deploy in Bluemix. Creating finally stream file for deployment in Bluemix.
- Once the finally stream file is ready then deploy into Bluemix with node.js web app. Using user input to predict heart failure risk with help of IBM SPSS Stream solution on Bluemix.
Environment
IBM Bluemix, Dash dB, IBM SPSS, C 5.0 modeling, IBM WebSphere 6.1, ECG IoT Simulator, Node RED, Cloudant, node.js, web app, predictive analytics, IBM Tester deploy, deployed in Bluemix.
Check out the for more info on how to get the most out of Balaji N. File all bugs/feature requests at BalajiN GitHub repo. If you have questions, you can ask me Balaji Talk.
