Applications of Big Data in Healthcare: Theory and Practice

By Ashish Khanna (Author), this book introduces the basics of Big Data analysis and its tools, processes, and procedures. It unites healthcare with Big Data analysis, leveraging the latter’s advantages to solve the former’s problems. The authors present the challenges faced by the healthcare industry, including capturing, storing, searching, sharing, and analyzing data.

Challenges in Healthcare Data Analysis

The healthcare industry faces numerous challenges in data analysis, including:

• Capturing and storing large amounts of data
• Searching and retrieving specific data points
• Sharing data securely across different systems
• Analyzing complex, noisy, and voluminous data

Overcoming Challenges with Big Data

This book illustrates the challenges in the applications of Big Data and suggests ways to overcome them, focusing on data repositories, challenges, and concepts for data scientists, engineers, and clinicians. It emphasizes the importance of personalized healthcare through the use of Big Data.

Case Studies and Applications

The book provides case studies that demonstrate the business processes underlying the use of Big Data and deep learning health analytics to improve healthcare delivery. These case studies showcase how Big Data can be used to:

• Improve patient care through personalized treatment plans
• Enhance operational efficiency in hospitals and clinics
• Reduce healthcare costs by identifying high-risk patients
• Improve drug development and clinical trials

Additional Resources

Readers will find links to websites, videos, articles, and other online content that expand and support the primary learning objectives for each major section of the book. These resources provide further insights into clinical analysis and data management, helping readers deepen their understanding of Big Data in healthcare.

ISBN: 9780128202036, 9780128204511

Language: English

Publisher: Elsevier Science

Publication Date: March 10, 2021