Artificial Intelligence: reshaping the practice of radiological sciences in the 21st century
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- Issam El Naqa
- Department of Radiation Oncology, University of Michigan , Ann Arbor, MI , USA
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- Masoom A Haider
- Department of Medical Imaging and Lunenfeld-Tanenbaum Research Institute, University of Toronto , Toronto, ON , Canada
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- Maryellen L Giger
- Department of Radiology, University of Chicago , Chicago, IL , USA
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- Randall K Ten Haken
- Department of Radiation Oncology, University of Michigan , Ann Arbor, MI , USA
説明
<jats:p>Advances in computing hardware and software platforms have led to the recent resurgence in artificial intelligence (AI) touching almost every aspect of our daily lives by its capability for automating complex tasks or providing superior predictive analytics. AI applications are currently spanning many diverse fields from economics to entertainment, to manufacturing, as well as medicine. Since modern AI’s inception decades ago, practitioners in radiological sciences have been pioneering its development and implementation in medicine, particularly in areas related to diagnostic imaging and therapy. In this anniversary article, we embark on a journey to reflect on the learned lessons from past AI’s chequered history. We further summarize the current status of AI in radiological sciences, highlighting, with examples, its impressive achievements and effect on re-shaping the practice of medical imaging and radiotherapy in the areas of computer-aided detection, diagnosis, prognosis, and decision support. Moving beyond the commercial hype of AI into reality, we discuss the current challenges to overcome, for AI to achieve its promised hope of providing better precision healthcare for each patient while reducing cost burden on their families and the society at large.</jats:p>
収録刊行物
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- The British Journal of Radiology
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The British Journal of Radiology 93 (1106), 20190855-, 2020-01-22
Oxford University Press (OUP)