1st Edition

Exploratory Data Analytics for Healthcare

    306 Pages 126 B/W Illustrations
    by CRC Press

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    Exploratory data analysis helps to recognize natural patterns hidden in the data. This book describes the tools for hypothesis generation by visualizing data through graphical representation and provides insight into advanced analytics concepts in an easy way. The book addresses the complete data visualization technologies workflow, explores basic and high-level concepts of computer science and engineering in medical science, and provides an overview of the clinical scientific research areas that enables smart diagnosis equipment. It will discuss techniques and tools used to explore large volumes of medical data and offers case studies that focus on the innovative technological upgradation and challenges faced today. The primary audience for the book includes specialists, researchers, graduates, designers, experts, physicians, and engineers who are doing research in this domain.

    Chapter 1 Visual Analytics: Scopes and Challenges

    Kalpana Hazarika, A. Ambikapathy, Shobana R., and Amit Agrawal

    Chapter 2 Statistical Methods and Applications: A Comprehensive Reference for the Healthcare Industry

    Areeba Kazim, Achyut Shankar, and Muskan Jindal

    Chapter 3 Machine Learning Algorithms for Healthcare Data Analytics

    G. Shyamala and Ilavendhan A.

    Chapter 4 A Review of Challenges and Opportunities in Machine Learning for Healthcare

    M. Arvindhan, D. Rajeshkumar, and Anupam Lakhan Pal

    Chapter 5 Digitalizing the Health Records Using Machine Learning Algorithms

    N. Pooranam, M. Diwakaran, and T. Vignesh

    Chapter 6 Interactive Visualization for Understanding and Analyzing Medical Data

    S. Suganthi and T. Poongodi

    Chapter 7 Heart Disease Prediction Using Tableau

    R. Indrakumari, Priyanka Shukla, and Akanksha Sehgal

    Chapter 8 A Deep Learning Framework Using AlexNet for Early Detection of Pancreatic Cancer

    Geraldine Bessie Amali, Gaurav Ramtri, Anukriti Kacker, and Siddharth Menon

    Chapter 9 Applications of the Map-Reduce Programming Framework to Clinical Big Data Analysis: Current Landscape and

    Future Trends

    Gagandeep Kaur, Satish Saini, and Sachin Minocha

    Chapter 10 An Investigation of Different Machine Learning Approaches for Healthcare Analytics

    Kayal Padmanandam

    Chapter 11 The Potential of Machine Learning for Clinical Predictive Analytics

    Kunal Pant, Nikhil Sati, Divyansh Agrawal, and Deepa Dangwal

    Chapter 12 Predictive Analytics in Healthcare Using Machine Learning Tools and Techniques

    Shobana R., A. Ambikapathy, Kalpana Hazarika, and Amit Kumar Gupta

    Chapter 13 A Collective Study of Machine Learning (ML) Algorithms and Its Impact on Various Facets of Healthcare

    Roshan Lal and Sandhya Tarar


    Dr. R. Lakshmana Kumar is an Assistant professor in the Computer Applications Department and currently also leading the technical training team in Hindusthan College of Engineering and Technology, Coimbatore. Tamil Nadu. His PhD is from Anna University, Chennai and his Research is on Semantic Web Services. Part of his PhD work was funded by South Korea. He is a global chapter lead for MLCS [Machine Learning for Cyber Security] for the Coimbatore chapter. He is currently allied with company-specific training of Infosys Campus Connect, Oracle WDP and Palo Alto Networks. He has a passion for software development and holds an international certification on SCJP (Sun Certificated Java Programmer) and SCJWCD (Sun Certificate Java Web Component Developer). He is familiar with programming languages like Java, Python, and PHP. He is involved with research and considered an expertise in distributed computing. He also holds the Data Science certification from John Hopkins University and the Amazon Cloud Architect certification from Amazon Web Services. He has published more than 25 papers in various international journals. Dr. R. Indrakumari is an Assistant Professor as the School of Computing Science and Engineering, Galgotias University, NCR Delhi, India. She has completed the M.Tech in Computer and Information Technology from Manonmaniam Sundaranar University, Tirunelveli. Her main areas of interest are Big Data, Internet of Things, Data Mining, Data warehousing and its visualization tools such as Tableau, Qlikview. Dr. B. Balamurugan Completed his PhD. at Vellore Institute of Technology University, Vellore and is currently working as a Professor at Galgotias University, Greater Noida, Uttar Pradesh. He has 15 years of teaching experience in the field of computer science. His area of interest lies in the field of Internet of Things, Big data, Networking. He has published more than 100 international journals papers and contributed book chapters. Dr. Achyut Shankar completed his PhD at Vellore Institute of Technology University, Tamilnadu, India and is currently working as an Assistant Professor at Amity School of Engineering and Technology, India. His areas of interested are Data Communication, Computer Networks, Machine Learning, Statistical Tools, Operating Systems, Pattern Recognition, and Theory of Computation.