Heart Disease Identification Method Using Machine Learning Classification in E-Healthcare

Heart Disease Identification Method Using Machine Learning Classification in E-Healthcare

₹5,500.00
Product Code: Python - Machine Learning
Availability: In Stock
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Product Description

Aim:

          To apply machine learning techniques resulting in improving the accuracy in the prediction of cardiovascular disease

Synopsis:

            Millions of people today are suffering from  various diseases that can prove fatal. Diseases like cancer,  heart diseases, diabetes, etc. cause a lot of health problems  which may  even lead to death. Identification of such diseases  in early stages can help solve a lot of conditions related to  them. Diagnosis of diseases at the right time will be of great  help. Therefore, to help the diagnosis process many data  mining and machine learning techniques can be used. Data  mining helps in finding out patterns in the data collected, by  utilizing data mining we can assess numerous examples which  will be used in the future to settle on wise frameworks and choices.  Data mining alludes to different strategies for distinguishing  data or the reception of arrangements dependent on learning  and information extraction of this information with the goal that they can be utilized in different territories, for decision  making and prediction calculation of probability. Present  health industry has a lot of information about patient’s  history. The huge amount of data can be scrutinized using  data mining techniques, later machine learning algorithms  can be used for the prediction process. Thus the main focus of  the system is to make use data analytics to predict the  presence of the disease and level of disease among patients.

 

 Proposed System

          ML process starts from a pre-processing data phase followed by feature selection based on data cleaning, classification of modeling, performance evaluation, and the results with improved accuracy. We create a web application through the user input to predict a heart disease.

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Package Includes

Software Projects Includes

  1. Demo  Video
  2. Abstract
  3. Base paper
  4. Full Project PPT
  5. UML Diagrams
  6. SRS
  7. Source Code
  8. Screen Shots
  9. Software Links
  10. Reference Papers
  11. Full Project Documentation
  12. Online support


The Delivery time for software projects is 2 -3 working days. Some of the software projects will require Hardware interface. Please go through the hardware Requirements in the abstract carefully. The Hardware will take 7-8 Working Days

 

Hardware Projects Includes

  1. Demo  Video
  2. Abstract
  3. Base paper
  4. Full Project PPT
  5. Datasheets
  6. Circuit Diagrams
  7. Source Code
  8. Screen Shots & Photos
  9. Software Links
  10. Reference Papers
  11. Lit survey
  12. Full Project Documentation
  13. Online support


The Delivery time for Hardware projects is 7-8 working days.

   

Mini Projects: Software Includes

  1. Demo  Video
  2. Abstract
  3. Base paper
  4. Full Project PPT
  5. UML Diagrams
  6. SRS
  7. Source Code
  8. Screen Shots
  9. Software Links
  10. Reference Papers
  11. Full Project Documentation
  12. Online support

 

The Delivery time for software Miniprojects is 2 -3 working days.

 

Mini Projects - Hardware includes

  1. Demo  Video
  2. Abstract
  3. PPT
  4. Datasheets
  5. Circuit Diagrams
  6. Source Code
  7. Screen Shots & Photos
  8. Software Links
  9. Reference Papers
  10. Full Project Documentation
  11. Online support

The Delivery time for Hardware Mini projects is 7-8 working days.