Smart Health Disease Prediction Using Naive Bayes in C#.Net

 

Smart Health Disease Prediction Using Naive Bayes

 

 PROJECT ID: C#NET25

 

PROJECT NAME: Smart Health Disease Prediction Using Naive Bayes

 

PROJECT CATEGORY: MCA / BCA / BCCA / MCM / POLY / ENGINEERING

 

PROJECT ABSTRACT:

It might have happened so many times that you or your closed ones need doctors help immediately, but they are not available due to some reasons. The Health Prediction system is an end user support and online consultation project. Here we propose a system that allows users to get instant guidance on their health issues through an intelligent health care system online. The system is fed with various symptoms and the disease/illness associated with those systems. This health prediction system allows users to share their symptoms and issues. It then processes user’s symptoms to check for various illness that could be associated with it. Here we use intelligent system of Naïve Bayes algorithm and depending on the symptoms will predict the diseases and for normal person it will predict the daily hygiene diet and routines which he/ she can follow. Users will also be able to contact the specialist doctors nearby. It will help users for easy medical treatment and diagnosis. Naïve Bayes algorithm urges users to go for blood test, x-ray, CITI scan or whichever report it feels user’s symptoms are associated with, so next time user may be able to login and upload an image of those reports. The system also has a doctor login, these uploaded images are now sent to respective doctor along with patient contact details. The doctors may now contact the patient for further process

SOFTWARE REQUIREMENTS:

FRONT END: ASP.NET

Technologies: C#,

DATABASE: SQL Server, IIS

Operating System: Windows XP/7/8/10

HARDWARE REQUIREMENTS:

Processor: Intel Pentium based system 

Processor speed:  250 MHz to 833MHz 

RAM SPEED:  1GB 

CONCLUSION

Decision Support in Heart Disease Prediction System is developed using Naive Bayesian Classification technique. The system extracts hidden knowledge from a historical heart disease database. This is the most effective model to predict patients with heart disease. This model could answer complex queries, each with its own strength with respect to ease of model interpretation, access to detailed information and accuracy. HDPS can be further enhanced and expanded. For, example it can incorporate other medical attributes besides the above list. It can also incorporate other data mining techniques. Continuous data can be used instead of just categorical data.

HDPS can be further enhanced and expanded. For example, it can incorporate other medical attributes besides the 15 listed in Figure 1.

It can also incorporate other data mining techniques, e.g., Time Series, Clustering and Association Rules. Continuous data can also be used instead of just categorical data. Another area is to use Text Mining to mine the vast amount of unstructured data available in healthcare databases. Another challenge would be to integrate data mining and text mining .

TABLE OF CONTENTS

·        Title Page      

·        Declaration

·        Certification Page

·        Dedication

·        Acknowledgements

·        Table of Contents

·        List of Tables

·        Abstract

 

CHAPTER SCHEME

CHAPTER ONE: INTRODUCTION

CHAPTER TWO: OBJECTIVES

CHAPTER THREE: PRELIMINARY SYSTEM ANALYSIS

·        Preliminary Investigation

·        Present System in Use

·        Flaws In Present System

·        Need Of New System

·        Feasibility Study

·        Project  Category

CHAPTER FOUR: SOFTWARE ENGINEERING AND PARADIGM APPLIED   

·        Modules

·        System / Module Chart

CHAPTER FIVE: SOFTWARE AND HARDWARE REQUIREMENT

CHAPTER SIX: DETAIL SYSTEM ANALYSIS

·        Data Flow Diagram

·        Number of modules and Process Logic

·        Data Structures  and Tables

·        Entity- Relationship Diagram

·        System Design

·        Form Design 

·        Source Code

·        Input Screen and Output Screen

CHAPTER SEVEN: TESTING AND VALIDATION CHECK

CHAPTER EIGHT: SYSTEM SECURITY MEASURES

CHAPTER NINE: IMPLEMENTATION, EVALUATION & MAINTENANCE

CHAPTER TEN: FUTURE SCOPE OF THE PROJECT

CHAPTER ELEVEN: SUGGESTION AND CONCLUSION

CHAPTER TWELE: BIBLIOGRAPHY& REFERENCES          

Other Information

 

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PROJECT WITH SPIRAL BINDING	1750/- Only
PROJECT WITH HARD BINDING	1850/- Only
TOTAL COST (SYNOPSIS, SOFTCOPY, HARDBOOK, and SOFTWARE, PPT)	2500/- Only
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