Provides insight on building smart sustainable solutions Includes details of applying mining, learning, IOT and sensor-based techniques for sustainable computing Entails data extraction from various sources followed with pre-processing of data, and how to make effective use of extracted data for application-based research Involves practical usage of data analytic language, including R, Python, etc. for improving sustainable services offered by multi-disciplinary domains Encompasses comparison and analysis of recent technologies and trends Includes development of smart models for information gain and effective decision making with visualization

About the Book The book provides details of applying intelligent mining techniques for extracting and pre-processing medical data from various sources, for application-based healthcare research. Moreover, different datasets are used, thereby exploring real-world case studies related to medical informatics. This book would provide insight to the learners about Machine Learning, Data Analytics, and Sustainable Computing. Salient Features of the Book Exhaustive coverage of Data Analysis using R Real-life healthcare models for: Visually Impaired Disease Diagnosis and Treatment options Applications of Big Data and Deep Learning in Healthcare Drug Discovery Complete guide to learn the knowledge discovery process, build versatile real life healthcare applications Compare and analyze recent healthcare technologies and trends Target Audience This book is mainly targeted at researchers, undergraduate, postgraduate students, academicians, and scholars working in the area of data science and its application to health sciences. Also, the book is beneficial for engineers who are engaged in developing actual healthcare solutions.