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: Deep learning techniques for biomedical and health informatics
  name:
    name part: Agarwal, Basant.
  name:
    name part: Balas, Valentina Emilia.
  name:
    name part: Jain, L. C.
  name:
    name part: Poonia, Ramesh C.
    name part: 1979-
  name:
    name part: Sharma, Manisha.
  name:
    name part: ScienceDirect (Online service)
  type of resource: text
  genre: bibliography
  genre: Electronic books.
  origin info:
    place:
      place term: enk
    date issued: 2020
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource (370 pages)
  abstract: Deep Learning Techniques for Biomedical and Health Informatics provides readers with the state-of-the-art in deep learning-based methods for biomedical and health informatics. The book covers not only the best-performing methods, it also presents implementation methods. The book includes all the prerequisite methodologies in each chapter so that new researchers and practitioners will find it very useful. Chapters go from basic methodology to advanced methods, including detailed descriptions of proposed approaches and comprehensive critical discussions on experimental results and how they are applied to Biomedical Engineering, Electronic Health Records, and medical image processing.- Examines a wide range of Deep Learning applications for Biomedical Engineering and Health Informatics, including Deep Learning for drug discovery, clinical decision support systems, disease diagnosis, prediction and monitoring- Discusses Deep Learning applied to Electronic Health Records (EHR), including health data structures and management, deep patient similarity learning, natural language processing, and how to improve clinical decision-making- Provides detailed coverage of Deep Learning for medical image processing, including optimizing medical big data, brain image analysis, brain tumor segmentation in MRI imaging, and the future of biomedical image analysis.
  note: edited by Basant Agarwal, Valentina Emilia Balas, Lakhmi C. Jain, Ramesh Chandra Poonia, Manisha.
  note: Includes bibliographical references and index.
  subject:
    topic: Machine learning
  subject:
    topic: Artificial intelligence
    topic: Medical applications
  subject:
    topic: Medicine
    topic: Data processing
  subject:
    topic: Deep learning (Machine learning)
  subject:
    topic: Deep Learning
  subject:
    topic: Medical Informatics
  subject:
    topic: Electronic Health Records
  subject:
    topic: Machine Learning
  subject:
    topic: Apprentissage automatique
  subject:
    topic: Intelligence artificielle
    topic: Applications en médecine
  subject:
    topic: Médecine
    topic: Informatique
  subject:
    topic: Apprentissage profond
  subject:
    topic: Artificial intelligence
    topic: Medical applications
  subject:
    topic: Machine learning
  subject:
    topic: Medicine
    topic: Data processing
  classification: Q325.5
  classification: 006.3/1
  related item:
    title info:
      title: Deep Learning Techniques for Biomedical and Health Informatics
    name:
      name part: Agarwal, Basant.
    origin info:
      publisher: San Diego : Elsevier Science & Technology, ©2020
  identifier: 9780128190623
  identifier: 0128190620
  identifier: 9780128190616
  identifier: 0128190612
  identifier: 9780128190623 Ingram Content Group
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: EBLCP
    record creation date: 200118
    record change date: 20260327164030.2
    record identifier: in00005765995
    language of cataloging:
      language term: eng