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Quality use of artificial intelligence in medical imaging: What do radiologists need to know?
Goergen, Stacy K; Frazer, Helen Ml; Reddy, Sandeep.
Affiliation
  • Goergen SK; Monash Imaging, Monash Health, Melbourne, Victoria, Australia.
  • Frazer HM; Department of Imaging, School of Clinical Sciences, Monash University, Melbourne, Victoria, Australia.
  • Reddy S; St Vincent's BreastScreen, St Vincent's Hospital Melbourne, Melbourne, Victoria, Australia.
J Med Imaging Radiat Oncol ; 66(2): 225-232, 2022 Mar.
Article in En | MEDLINE | ID: mdl-35243782
ABSTRACT
The application of artificial intelligence, and in particular machine learning, to the practice of radiology, is already impacting the quality of imaging care. It will increasingly do so in the future. Radiologists need to be aware of factors that govern the quality of these tools at the development, regulatory and clinical implementation stages in order to make judicious decisions about their use in daily practice.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Radiology / Artificial Intelligence Type of study: Diagnostic_studies / Prognostic_studies Limits: Humans Language: En Journal: J Med Imaging Radiat Oncol Journal subject: DIAGNOSTICO POR IMAGEM / NEOPLASIAS / RADIOLOGIA Year: 2022 Document type: Article Affiliation country:

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Radiology / Artificial Intelligence Type of study: Diagnostic_studies / Prognostic_studies Limits: Humans Language: En Journal: J Med Imaging Radiat Oncol Journal subject: DIAGNOSTICO POR IMAGEM / NEOPLASIAS / RADIOLOGIA Year: 2022 Document type: Article Affiliation country: