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: Machine learning approaches and applications in applied intelligence for healthcare data analytics
  name:
    name part: Kumar, Abhishek
    role:
      role term: editor.
  name:
    name part: Sreenatha, Anavatti G.
    role:
      role term: editor.
  name:
    name part: Dubey, Ashutosh Kumar
    role:
      role term: editor.
  name:
    name part: Rathore, Pramod Singh
    name part: 1988-
    role:
      role term: editor.
  name:
    name part: EBSCOhost
  type of resource: text
  genre: bibliography
  genre: Electronic books.
  origin info:
    place:
      place term: flu
    date issued: 2022
    copyright date: 2022
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource.
  table of contents: 1. Machine Learning in Healthcare. 2. Feature Extraction and Applications of Bio Signals. 3. Machine Learning Methods for Managing Parkinson⁰́₉s Disease. 4. Challenges of Medical Text and Image Processing. 5. Machine Learning Solutions in Computer-Aided Medical Diagnosis. 6. Rule Learning in Healthcare and Health Services Research. 7. Diagnosis in Medical Imaging. 8. Identifying Diseases and Diagnosis Using Machine Learning. 9. Machine Learning-Based Behavioral Modification. 10. Smart Health Records. 11. Treatment Recommendation System. 12. Smart Health Informatics System. 13. Natural Language Processing Utilization in Healthcare. 14. Clinical Decision Support and Predictive Analytics. 15. Bioinformatics and Biometrics. 16. Human Computer Interfaces and Usability. 17. Education and Capacity Building. 18. Learning Analytics for Competence Assessment. 19. Patient Simulators. 20. Serious Gaming. 21. Patient Empowerment and Engagement. 22. Social Media, Mobile Apps, and Patient Portals. 23. Human Factors and Technology Adoption. 24. Surveillance System. 25. Robotics. 26. Object Detection. 27. Traffic Analysis. 28. Big Data in Healthcare Systems. 29. Advanced Decision-Making and Data Analytics. 30. Emergence of Decision Support Systems. 31. Big Data Based Frameworks and Machine Learning. 32. Predictive Analysis and Modeling. 33. Security and Privacy with Machine Learning Systems. 34. Role of Social Media in Healthcare Analytics. 35. Big Data Based Case Studies for Healthcare Analytics. 36. Machine Learning and Deep Learning Paradigms and Case Studies. 37. Machine Learning in Agriculture.
  note: edited by Abhishek Kumar, Anavatti G. Sreenatha, Ashutosh Kumar Dubey, and Pramod Singh Rathore.
  note: Includes bibliographical references and index.
  subject:
    topic: Medical informatics
  subject:
    topic: TECHNOLOGY / Operations Research
  subject:
    topic: Medical informatics
  classification: R858 .M33 2022
  classification: 610.285
  related item:
    title info:
      title: Innovations in big data and machine learning
  related item:
    title info:
      title: Machine learning approaches and applications in applied intelligence for healthcare data analytics
    origin info:
      publisher: Boca Raton : CRC Press, 2022
      edition: First edition.
    identifier: (DLC) 2021043556
  identifier: 9781003132110
  identifier: 1003132111
  identifier: 9781000539974
  identifier: 1000539970
  identifier: 9781000539981
  identifier: 1000539989
  identifier: 9780367676339
  identifier: 9780367676346
  identifier: 2021043557
  identifier: 9781003132110 Taylor & Francis
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: DLC
    record creation date: 211021
    record change date: 20220512144355.0
    record identifier: in00004599006
    language of cataloging:
      language term: eng