scholarly journals Comparison of skin disease prediction by feature selection using ensemble data mining techniques

2019 ◽  
Vol 16 ◽  
pp. 100202 ◽  
Author(s):  
Anurag Kumar Verma ◽  
Saurabh Pal ◽  
Surjeet Kumar
Keyword(s):  
Data Mining ◽  
Feature Selection ◽  
Skin Disease ◽  
Disease Prediction ◽  
Data Mining Techniques ◽  
Ensemble Data

scholarly journals Classification of Skin Disease using Ensemble Data Mining Techniques

2019 ◽  
Vol 20 (6) ◽  
pp. 1887-1894 ◽  
Author(s):  
Anurag Kumar Verma ◽  
Saurabh Pal ◽  
Surjeet Kumar
Keyword(s):  
Data Mining ◽  
Skin Disease ◽  
Data Mining Techniques ◽  
Ensemble Data

Heart disease prediction using data mining techniques

2017 ◽  
Author(s):  
Abhishek Rairikar ◽  
Vedant Kulkarni ◽  
Vikas Sabale ◽  
Harshavardhan Kale ◽  
Anuradha Lamgunde
Keyword(s):  
Data Mining ◽  
Heart Disease ◽  
Disease Prediction ◽  
Data Mining Techniques ◽  
Using Data

Cardiovascular Disease Prediction Using Data Mining Techniques

2019 ◽  
pp. 246-264
Author(s):  
Kalyani Kadam ◽  
Pooja Vinayak Kamat ◽  
Amita P. Malav
Keyword(s):  
Data Mining ◽  
Cardiovascular Disease ◽  
Big Data ◽  
Cardiovascular Diseases ◽  
Primary Objective ◽  
Disease Prediction ◽  
Data Mining Techniques ◽  
Data Architecture ◽  
Life Threatening ◽  
Using Data

Cardiovascular diseases (CVDs) have turned out to be one of the life-threatening diseases in recent times. The key to effectively managing this is to analyze a huge amount of datasets and effectively mine it to predict and further prevent heart-related diseases. The primary objective of this chapter is to understand and survey various information mining strategies to efficiently determine occurrence of CVDs and also propose a big data architecture for the same. The authors make use of Apache Spark for the implementation.

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