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: Big data and artificial intelligence for healthcare applications
  name:
    name part: Saxena, Ankur
    role:
      role term: editor.
  name:
    name part: Brault, Nicolas
    role:
      role term: editor.
  name:
    name part: Rashid, Shazia
    role:
      role term: editor.
  name:
    name part: Taylor & Francis
  type of resource: text
  genre: bibliography
  genre: Electronic books.
  origin info:
    place:
      place term: flu
    date issued: 2021
    edition: First edition.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource
  abstract: "This book covers a wide range of topics on the role of Artificial Intelligence, Machine Learning, and Big Data for healthcare applications and deals with the ethical issues and concerns associated with it. This book explores the applications in different areas of healthcare and highlights the current research. The book covers healthcare big data analytics, mobile health and personalized medicine, clinical trial data management and presents how Artificial Intelligence can be used for early disease diagnosis prediction and prognosis. It also offers some case studies that describes the application of Artificial Intelligence and Machine Learning in healthcare. This book will be useful for researchers, healthcare professionals, data scientists, systems engineers, students, programmers, clinicians, and policymakers"--
  table of contents: Introduction to big data -- Introduction to machine learning -- Machine learning in clinical trials : a new era -- Deep learning and its biological and biomedical applications -- Application of machine learning algorithms to cancer data -- Pancreatic cancer detection by integrated level set based deep learning model -- Precision oriented detection of cervical cancer : a deep learning based framework -- Transformation of mHealth in the society -- Artificial intelligence and deep learning for medical diagnosis and treatment -- Ethical issues and challenges with artificial intelligence in healthcare -- Epistemological issues and challenges with artificial intelligence in healthcare.
  note: edited by Ankur Saxena, Nicolas Brault, and Shazia Rashid.
  note: Includes bibliographical references and index.
  subject:
    topic: Medical informatics
    topic: Technological innovations
  subject:
    topic: Medical telematics
    topic: Technological innovations
  subject:
    topic: Big data
  subject:
    topic: Data mining
  subject:
    topic: Artificial intelligence
    topic: Medical applications
  subject:
    topic: Data Mining
  subject:
    topic: Médecine
    topic: Informatique
    topic: Innovations
  subject:
    topic: Télématique médicale
    topic: Innovations
  subject:
    topic: Données volumineuses
  subject:
    topic: Exploration de données (Informatique)
  subject:
    topic: Intelligence artificielle
    topic: Applications en médecine
  subject:
    topic: COMPUTERS / Data Modeling & Design
  subject:
    topic: Artificial intelligence
    topic: Medical applications
  subject:
    topic: Big data
  subject:
    topic: Data mining
  classification: R858.A3
  classification: 610.285
  related item:
    title info:
      title: Big data and artificial intelligence for healthcare applications
    origin info:
      publisher: Boca Raton : CRC Press, 2021.
      edition: First edition.
    identifier: (DLC) 2020056220
  related item:
    title info:
      title: Big Data for Industry 4.0
  identifier: 9781003093770
  identifier: 1003093779
  identifier: 9780367554958
  identifier: 9781000387322
  identifier: 1000387321
  identifier: 9781000387315
  identifier: 1000387313
  identifier: 2020056221
  identifier: 9781000387322 Ingram Content Group
  identifier: 9781003093770 Taylor & Francis
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: DLC
    record creation date: 210207
    record change date: 20241108165922.3
    record identifier: in00005524852
    language of cataloging:
      language term: eng