Feature Extraction and Disease Prediction from Paddy Crops Using Data Mining Techniques

2020 ◽  
pp. 155-163 ◽  
Author(s):  
Sunanda Das ◽  
Shampa Sengupta
Keyword(s):  
Data Mining ◽  
Feature Extraction ◽  
Disease Prediction ◽  
Data Mining Techniques ◽  
Using 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.

scholarly journals Effective heart disease prediction system using data mining techniques

2018 ◽  
Vol Volume 13 ◽  
pp. 121-124 ◽  
Author(s):  
Poornima Singh ◽  
Sanjay Singh ◽  
Gayatri S Pandi-Jain
Keyword(s):  
Data Mining ◽  
Heart Disease ◽  
Disease Prediction ◽  
Prediction System ◽  
Data Mining Techniques ◽  
Using Data

Cardiovascular Disease Prediction Using Data Mining Techniques

2019 ◽  
pp. 159-179
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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