NLU Meghalaya Library

Online Public Access Catalogue (OPAC)

Amazon cover image
Image from Amazon.com

Exploratory data analytics for healthcare / edited by R. Lakshmana Kumar, R. Indrakumari, B. Balamurugan, Achyut Shankar.

Contributor(s): Material type: TextTextSeries: Innovations in big data and machine learningPublisher: Boca Raton, FL : CRC Press, 2022Edition: First editionDescription: 1 online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781003050827
  • 1003050824
  • 9781000527056
  • 1000527050
  • 9781000527018
  • 1000527018
Subject(s): DDC classification:
  • 610.285 23
LOC classification:
  • R858
Online resources:
Partial contents:
Visual analytics: scopes & challenges / K. Hazarika, GCET, Gr. Noida, India, M-IEEE, Dr. A. Ambikapathy, GCET, Gr. Noida, India, M-IEEE, Shobana R., GCET, Gr. Noida, India, M-IEEE, Dr. Amit Agrawal (ABES Engineering College, Ghaziabad, India -- Statistical methods and applications: a comprehensive reference for the healthcare industry / Areeba Kazim, Researcher, DST Project, Amity School of Engineering & Technology, Dept. of CSE, Amity University, Noida, UP, India, Dr. Achyut Shankar, Assistant Professor, Amity School of Engineering & Technology, Dept. of CSE, Amity University, Noida, UP, India, Muskan Jindal, Bachelors of Technology (Computer Science), Amity School of Engineering & Technology, Dept. of CSE, Amity University, Noida, UP, India -- Machine Learning Algorithms for Healthcare Data Analytic -- A review of challenges and opportunities in machine learning for healthcare / M. Arvindhan, Galgotias University, D. Rajeshkumar, Galgotias University.
Summary: "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"-- Provided by publisher.
Tags from this library: No tags from this library for this title. Log in to add tags.
Star ratings
    Average rating: 0.0 (0 votes)
No physical items for this record

Includes index.

Visual analytics: scopes & challenges / K. Hazarika, GCET, Gr. Noida, India, M-IEEE, Dr. A. Ambikapathy, GCET, Gr. Noida, India, M-IEEE, Shobana R., GCET, Gr. Noida, India, M-IEEE, Dr. Amit Agrawal (ABES Engineering College, Ghaziabad, India -- Statistical methods and applications: a comprehensive reference for the healthcare industry / Areeba Kazim, Researcher, DST Project, Amity School of Engineering & Technology, Dept. of CSE, Amity University, Noida, UP, India, Dr. Achyut Shankar, Assistant Professor, Amity School of Engineering & Technology, Dept. of CSE, Amity University, Noida, UP, India, Muskan Jindal, Bachelors of Technology (Computer Science), Amity School of Engineering & Technology, Dept. of CSE, Amity University, Noida, UP, India -- Machine Learning Algorithms for Healthcare Data Analytic -- A review of challenges and opportunities in machine learning for healthcare / M. Arvindhan, Galgotias University, D. Rajeshkumar, Galgotias University.

"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"-- Provided by publisher.

OCLC-licensed vendor bibliographic record.

There are no comments on this title.

to post a comment.
© 2022- NLU Meghalaya. All Rights Reserved. || Implemented and Customized by
OPAC Visitors

Powered by Koha