Applying Big Data Analytics in Bioinformatics and Medicine
Book information
Description
Many aspects of modern life have become personalized, yet healthcare practices have been lagging behind in this trend. It is now becoming more common to use big data analysis to improve current healthcare and medicinal systems, and offer better health services to all citizens. Applying Big Data Analytics in Bioinformatics and Medicine is a comprehensive reference source that overviews the current state of medical treatments and systems and offers emerging solutions for a more personalized approach to the healthcare field. Featuring coverage on relevant topics that include smart data, proteomics, medical data storage, and drug design, this publication is an ideal resource for medical professionals, healthcare practitioners, academicians, and researchers interested in the latest trends and techniques in personalized medicine. Title Page Copyright Page Book Series Table of Contents Detailed Table of Contents Preface Acknowledgment Section 1: Introduction to Bioinformatics in Medicine and Medical Systems Chapter 1: Bioinformatics as Applied to Medicine Chapter 2: Bioinformatics Chapter 3: Protein Structure Prediction Chapter 4: Proteomics in Personalized Medicine Chapter 5: The Much Needed Security and Data Reforms of Cloud Computing in Medical Data Storage Section 2: Bioinformatics in the Fields of Genomics and Proteomics as Applied to Medicine, Health Issues, and Medical Systems Chapter 6: Informatics and Data Analytics to Support Exposome-Based Discovery Chapter 7: Informatics and Data Analytics to Support Exposome-Based Discovery Chapter 8: Transcriptomics to Metabolomics Chapter 9: Protein Docking and Drug Design Section 3: Big Data Analytics for Medical and Health informatics Chapter 10: Effective and Efficient Business Intelligence Dashboard Design Chapter 11: Role of Online Data from Search Engine and Social Media in Healthcare Informatics Chapter 12: An Optimized Semi-Supervised Learning Approach for High Dimensional Datasets Chapter 13: Predicting Patterns in Hospital Admission Data Chapter 14: Selection of Pathway Markers for Cancer Using Collaborative Binary Multi-Swarm Optimization Chapter 15: Applying Bayesian Networks in the Early Diagnosis of Bulimia and Anorexia Nervosa in Adolescents Chapter 16: Image Processing Including Medical Liver Imaging Compilation of References About the Contributors Index
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