PDD Predictive Diabetes Diagnosis using Data mining Algorithms

Project Code :TCMAJA590

Objective

The main goal of the project is "Predictive Analytics in Healthcare is mainly used to diagnose patients with diabetes, asthma, heart disease and another complex Diabetes disease."

Abstract

Data analytics is used to obtain useful insights from small or large data set to conclude some useful information and also used for future recommendation and decision making. Predictive Analytics uses data mining, machine learning techniques to make predictions about the future. It involves the analysis of available data. 

The predictive analytics in health care is primarily used to determine patients having initial stages of diabetes, asthma, heart disease, and another critical lifetime disease. The proposed method of PDD uses data mining algorithms to predict type2 diabetes. The data mining algorithms used in the proposed system are K-Means Clustering and Random Forest. The predictive model, PDD provides better results in terms of accuracy when compared to hierarchical clustering and Bayesian network clustering with random forest prediction.

Keywords: Type 2 diabetes, Prediction, K-Means Clustering, Random Forest

NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.

Block Diagram

Specifications

H/W SYSTEM SPECIFICATIONS:

  • Processor: I3/Intel Processor
  • RAM: 8 GB (min)
  • Hard Disk: 160 GB
  • Key Board: Standard Windows Keyboard
  • Mouse: Two or Three Button Mouse
  • Monitor: SVGA

 S/W SYSTEM SPECIFICATIONS:

  • Operating System: Windows 7 or 8 32 bit                
  • Backend coding: Java
  • Tool: Virtual Box
  • Environment: Ubuntu
  • Technology: Hadoop

 

Learning Outcomes

  • Scope of  Real Time  Application Scenarios
  • How Internet Works
  • What is a  search engine  and how browser can work
  • What is Tomcat  server and how they can work
  • What type of technology versions are used
  • Use of HTML and CSS on UI Designs
  • Data Base Connections
  • Data Parsing Front-End to Back-End
  • Need of  Eclipse-IDE to Develop a web application
  • Working Procedure
  • Testing Techniques
  • Error Correction mechanisms
  • How to run and Deploy the applications
  • Introduction to basic technologies used for
  • How project works.
  • Input and Output modules
  • How test the project based on user inputs and observe the output
  • Project Development Skills:
    • Problem analyzing skills.
    • Problem solving skills.
    • Creativity and imaginary skills.
    • Programming skills.
    • Deployment.
    • Testing skills.
    • Debugging skills.
    • Project presentation skills.
    • Thesis writing skills.

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