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Intelligent Learning Analytics in Healthcare Sector Using Machine Learning

  • Pratiyush GuleriaEmail author
  • Manu Sood
Chapter
  • 19 Downloads
Part of the Learning and Analytics in Intelligent Systems book series (LAIS, volume 13)

Abstract

Machine Learning and its role in the health care sector is the area of research in emerging times. There are learning types in Machine Learning which involves Supervised, Unsupervised and Reinforcement Learning. These techniques become important to unearth the hitherto unknown relationship from data which become useful for society. In the proposed chapter, the author has discussed the intelligent learning analytics achieved using Machine Learning and predicted the patient prognosis based on the input dataset values using python. Here, predictive modeling is done that uses historical data to predict an output variable. The Machine Learning applications in healthcare are becoming boon to patients for identifying diseases and diagnostics. The Healthcare sector can benefit from the ability of technologies such as Machine Learning to support them in the intelligent analysis of vast amount of data. Machine Learning in Healthcare sector helps to analyze the data and predict the outcome. The intelligent learning analytics achieved through Machine Learning can break down information to enable it to make predictions.

Keywords

Emerging Health Learning Predicted Reinforcement Supervised Unsupervised 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.NIELIT ShimlaShimlaIndia
  2. 2.Department of Computer ScienceHimachal Pradesh UniversityShimlaIndia

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