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Efficacy of Knowledge Mining and Machine Learning Techniques in Healthcare Industry

Chapter

Abstract

Knowledge mining is the process of discovering the knowledge from the larger database. As the size of the data is increasing enormously in the healthcare industry knowledge mining techniques are used to extract and mine the dataset to acquire new knowledge. Machine learning is a technique of training the system. In connection with artificial intelligence, statistics, and computer science, it is also known as statistical learning or predictive analytics. In recent years, application of machine learning and knowledge mining methods is been used everywhere in daily life. Healthcare system can cater prime diagnosis data of human healthcare details and reference to the doctors. Historical medical records afford other healthcare providers to access quickly and recognize the patients past and current health status. Chronic obstructive pulmonary disease is becoming one of the causes for leading deaths. An experiment is conducted to predict the presence and severity of the chronic obstructive pulmonary diseases (COPDs) using knowledge mining and machine learning techniques. Logistic and multinominal regression has been implemented to predict the prevalence of the disease using attributes from various sources and structures.

Keywords

Chronic obstructive pulmonary disease (COPD) Machine learning Logistic regression Multinomial logistic regression Regression analysis 

Notes

Acknowledgements

We would like to express our special thanks of gratitude and deep regards to Dr. Yunus Sheriff pursuing DNB Pulmonology for his classic guidance, appreciated feedback and constant encouragement in understanding COPD and analyze the complications. His valuable suggestions were of immense help to us in getting this work done.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Department of MCAR V College of EngineeringBengaluruIndia

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