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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. 1. Big Data Analysis in Healthcare 2. Smart EHR for Healthcare 3. Lifestyle Application for Visually Impaired 4. Classification of Genetic Mutation 5. MHealth: Community-based Android Application for Medical Services 6. Nanoemulsions: Status in Antimicrobial Therapy 7. Analysis of Air Quality and Impacts on Human Health 8. Brain Tumor Detection and Classification in MRI: Technique for Smart Healthcare Adaptation 9. Deep Strategies in Computer Assisted Diagnosis and Classification of Abnormalities in Medical Images 10. Major Histocompatibility Complex Binding and various health parameters analysis 11. Partial Digest Problem 12. Deep Learning for Next Generation Healthcare: A Survey of State-of-the-art and Research Prospects 13. Applications of Protein Nanoparticles as Drug Delivery Vehicle 14. Exploring Food Domain using Deep Neural Networks Dr. Adwitiya Sinha received her PhD from Jawaharlal Nehru University (JNU), New Delhi. She is a recipient of a Senior Research Fellowship from CSIR, New Delhi, India and a UGC Research Scholarship. Her application-based research is mainly focused on large-scale graphs, data analytics, and confluence of sensor-based applications with social networking. Megha Rathi has 10 years of teaching experience. She has worked on the Xform generator research project of at NIC, Delhi. She has experience in software development and worked as a Project Associate at IIT Delhi. Her research areas include Data Mining, Data Science Analytics, Health Science, and Machine Learning.