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Journal of Nuclear Medicine Technology

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OtherContinuing Education

Intelligent Imaging: Anatomy of Machine Learning and Deep Learning

Geoffrey M Currie
Journal of Nuclear Medicine Technology August 2019, jnmt.119.232470; DOI: https://doi.org/10.2967/jnmt.119.232470
Geoffrey M Currie
Charles Sturt University, Australia
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Abstract

The emergence of artificial intelligence (AI) in nuclear medicine and radiology has been accompanied by AI commentators and experts predicted that AI would make radiologists in particular extinct. More realistic perspectives suggest significant changes will occur in medical practice. There is no escaping the disruptive technology associated with AI, neural networks and deep learning; the most significant perhaps since the early days of Roentgen, Becquerel and Curie. AI is an omen, but it need not be foreshadowing a negative event but rather heralding great opportunity. The key to sustainability lies not in resisting AI but in having a deep understanding and exploiting the capabilities of AI in nuclear medicine while mastering those capabilities unique to the human resources.

  • Statistical Analysis
  • Other
  • artificial intelligence
  • artificial neural network
  • deep learning
  • machine learning
  • nuclear medicine
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In this issue

Journal of Nuclear Medicine Technology: 53 (1)
Journal of Nuclear Medicine Technology
Vol. 53, Issue 1
March 1, 2025
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Intelligent Imaging: Anatomy of Machine Learning and Deep Learning
Geoffrey M Currie
Journal of Nuclear Medicine Technology Aug 2019, jnmt.119.232470; DOI: 10.2967/jnmt.119.232470

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Intelligent Imaging: Anatomy of Machine Learning and Deep Learning
Geoffrey M Currie
Journal of Nuclear Medicine Technology Aug 2019, jnmt.119.232470; DOI: 10.2967/jnmt.119.232470
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Keywords

  • statistical analysis
  • Other
  • artificial intelligence
  • artificial neural network
  • deep learning
  • machine learning
  • nuclear medicine
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