rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Exploratory data analytics for healthcare
  name:
    name part: Kumar, R. Lakshmana
    role:
      role term: editor.
  name:
    name part: Indrakumari, R.
    role:
      role term: editor.
  name:
    name part: Balamurugan, B.
    role:
      role term: editor.
  name:
    name part: Shankar, Achyut
    role:
      role term: editor.
  name:
    name part: Taylor & Francis
  type of resource: text
  genre: bibliography
  genre: Electronic books.
  genre: Case studies
  origin info:
    place:
      place term: flu
    date issued: 2022
    edition: First edition.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource.
  abstract: "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"--
  table of 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.
  note: edited by R. Lakshmana Kumar, R. Indrakumari, B. Balamurugan, Achyut Shankar.
  note: Includes bibliographical references and index.
  subject:
    topic: Medical informatics
    topic: Research
  subject:
    topic: Medicine
    topic: Data processing
    genre: Case studies
  subject:
    topic: Médecine
    topic: Informatique
    topic: Recherche
  subject:
    topic: Médecine
    topic: Informatique
    genre: Études de cas
  subject:
    topic: COMPUTERS / Computer Vision & Pattern Recognition
  subject:
    topic: Medicine
    topic: Data processing
  classification: R858
  classification: 610.285
  related item:
    title info:
      title: Innovations in big data and machine learning
  related item:
    title info:
      title: Exploratory data analytics for healthcare
    origin info:
      publisher: Boca Raton, FL : CRC Press, 2022
      edition: First edition.
    identifier: (DLC) 2021042071
  identifier: 9781000527056
  identifier: 1000527050
  identifier: 9781003050827
  identifier: 1003050824
  identifier: 9780367506919
  identifier: 9780367506926
  identifier: 9781000527018
  identifier: 1000527018
  identifier: 2021042072
  identifier: 9781003050827 Taylor & Francis
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: DLC
    record creation date: 210825
    record change date: 20241108165734.0
    record identifier: in00005522492
    language of cataloging:
      language term: eng