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: Radiomics and its clinical application
    sub title: artificial intelligence and medical big data
  name:
    name part: Tian, Jie
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Dong, Di
    role:
      role term: author.
  name:
    name part: Liu, Zhenyu
    role:
      role term: author.
  name:
    name part: Wei, Jingwei
    role:
      role term: author.
  name:
    name part: ScienceDirect (Online service)
  type of resource: text
  genre: Electronic books.
  origin info:
    place:
      place term: ne
    date issued: 2021
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource (1 volume)
  abstract: The rapid development of artificial intelligence technology in medical data analysis has led to the concept of radiomics. This book introduces the essential and latest technologies in radiomics, such as imaging segmentation, quantitative imaging feature extraction, and machine learning methods for model construction and performance evaluation, providing invaluable guidance for the researcher entering the field.It fully describes three key aspects of radiomic clinical practice: precision diagnosis, the therapeutic effect, and prognostic evaluation, which make radiomics a powerful tool in the clinical setting.This book is a very useful resource for scientists and computer engineers in machine learning and medical image analysis, scientists focusing on antineoplastic drugs, and radiologists, pathologists, oncologists, as well as surgeons wanting to understand radiomics and its potential in clinical practice.- An introduction to the concepts of radiomics- In-depth presentation of the core technologies and methods- Summary of current radiomics research, perspective on the future of radiomics and the challenges ahead- An introduction to several platforms that are planned to be built: cooperation, data sharing, software, and application platforms.
  note: Jie Tian, Di Dong, Zhenyu Liu, Jingwei Wei.
  subject:
    topic: Medical radiology
  subject:
    topic: Diagnostic imaging
    topic: Data processing
  subject:
    topic: Artificial intelligence
    topic: Medical applications
  subject:
    topic: Big data
  subject:
    topic: Radiologie médicale
  subject:
    topic: Imagerie pour le diagnostic
    topic: Informatique
  subject:
    topic: Intelligence artificielle
    topic: Applications en médecine
  subject:
    topic: Données volumineuses
  subject:
    topic: Artificial intelligence
    topic: Medical applications
  subject:
    topic: Big data
  subject:
    topic: Diagnostic imaging
    topic: Data processing
  subject:
    topic: Medical radiology
  classification: R895
  classification: 616.07570285
  related item:
    title info:
      title: The MICCAI Society book Series
  related item:
    title info:
      title: Radiomics and its clinical application
    name:
      name part: Tian, Jie.
    origin info:
      publisher: Amsterdam : Academic Press, 2021
    identifier: (OCoLC)1242845802
  identifier: 9780128181027
  identifier: 0128181028
  identifier: 9780128181010
  identifier: 012818101X
  identifier: 9780128181027 Ingram Content Group
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: N$T
    record creation date: 210614
    record change date: 20260327170433.6
    record identifier: in00005768325
    language of cataloging:
      language term: eng