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 analytics and machine intelligence in biomedical and health informatics
    sub title: concepts, methodologies, tools and applications
  name:
    name part: Dhal, Sunil Kumar
    role:
      role term: editor.
  type of resource: text
  genre: bibliography
  origin info:
    place:
      place term: mau
    date issued: 2022
    copyright date: 2022
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource : illustrations (chiefly color)
  abstract: Provides coverage of developments and state-of-the-art methods in the broad and diversified data analytics field and applicable areas such as big data analytics, data mining, and machine intelligence in biomedical and health informatics. The novel applications of Big Data Analytics and machine intelligence in the biomedical and healthcare sector is an emerging field comprising computer science, medicine, biology, natural environmental engineering, and pattern recognition. Biomedical and health informatics is a new era that brings tremendous opportunities and challenges due to the plentifully available biomedical data and the aim is to ensure high-quality and efficient healthcare by analyzing the data. The 12 chapters in??Big Data Analytics and Machine Intelligence in Biomedical and Health Informatics??cover the latest advances and developments in health informatics, data mining, machine learning, and artificial intelligence. They have been organized with respect to the similarity of topics addressed, ranging from issues pertaining to the Internet of Things (IoT) for biomedical engineering and health informatics, computational intelligence for medical data processing, and Internet of Medical Things??(IoMT). New researchers and practitioners working in the field will benefit from reading the book as they can quickly ascertain the best performing methods and compare the different approaches. Audience Researchers and practitioners working in the fields of biomedicine, health informatics, big data analytics, Internet of Things, and machine learning.
  table of contents: Front Matter -- An Introduction to Big Data Analytics Techniques in Healthcare / Anil Audumbar Pise -- Identify Determinants of Infant and Child Mortality Based Using Machine Learning: Case Study on Ethiopia / Sudhir Kumar Mohapatra, Srinivas Prasad, Getachew Mekuria Habtemariam, Mohammed Siddique -- Pre-Trained CNN Models in Early Alzheimer's Prediction Using Post-Processed MRI / Kalyani Gunda, Pradeepini Gera -- Robust Segmentation Algorithms for Retinal Blood Vessels, Optic Disc, and Optic Cup of Retinal Images in Medical Imaging / Birendra Biswal, T Raveendra, Dwiti Krishna Bebarta, P Geetha Pavani, PK Biswal -- Analysis of Healthcare Systems Using Computational Approaches / Hemanta Kumar Bhuyan, Subhendu Kumar Pani -- Expert Systems in Behavioral and Mental Healthcare: Applications of AI in Decision-Making and Consultancy / Shrikaant Kulkarni -- A Mathematical-Based Epidemic Model to Prevent and Control Outbreak of Corona Virus 2019 (COVID-19) / Shanmuk Srinivas Amiripalli, Vishnu Vardhan Reddy Kollu, Ritika Prasad, Mukkamala SNV Jitendra -- An Access Authorization Mechanism for Electronic Health Records of Blockchain to Sheathe Fragile Information / K Sowjanya Naidu, Srinivasa L Chakravarthy -- An Epidemic Graph's Modeling Application to the COVID-19 Outbreak / Hemanta Kumar Bhuyan, Subhendu Kumar Pani -- Big Data and Data Mining in e-Health: Legal Issues and Challenges / Amita Verma, Arpit Bansal -- Basic Scientific and Clinical Applications / Manna Sheela Rani Chetty, C V Kiran Babu -- Healthcare Branding Through Service Quality / Saraju Prasad, Sunil Dhal -- Index
  note: edited by Sunil Kumar Dhal [and three others].
  note: Includes bibliographical references and index.
  subject:
    topic: Medical informatics
  subject:
    topic: Big data
  subject:
    topic: Artificial intelligence
  subject:
    topic: Artificial intelligence
  subject:
    topic: Big data
  subject:
    topic: Medical informatics
  classification: R858 .B54 2022
  classification: 610.285
  related item:
    identifier: (OCoLC)1273337496
  identifier: 9781119792376
  identifier: 1119792371
  identifier: 9781119792369
  identifier: 1119792363
  identifier: 1119791731
  identifier: 9781119791737
  identifier: 9781119791737 O'Reilly Media
  identifier: https://proxy.library.tamu.edu/login
  record info:
    record content source: YDX
    record creation date: 220511
    record change date: 20260128205552.1
    record identifier: in00004671033
    language of cataloging:
      language term: eng