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Artificial intelligence in oncology

Cancer science, 2020-05, Vol.111 (5), p.1452-1460 [Peer Reviewed Journal]

2020 The Authors. published by John Wiley & Sons Australia, Ltd on behalf of Japanese Cancer Association. ;2020 The Authors. Cancer Science published by John Wiley & Sons Australia, Ltd on behalf of Japanese Cancer Association. ;2020. This work is published under http://creativecommons.org/licenses/by-nc/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1347-9032 ;EISSN: 1349-7006 ;DOI: 10.1111/cas.14377 ;PMID: 32133724

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  • Title:
    Artificial intelligence in oncology
  • Author: Shimizu, Hideyuki ; Nakayama, Keiichi I.
  • Subjects: Algorithms ; Artificial intelligence ; Cancer ; Deep learning ; Dermatology ; Industrialized nations ; Machine learning ; Mammography ; Medical research ; Medical screening ; Neural networks ; Oncology ; Pathology ; personalized medicine ; Researchers ; Review
  • Is Part Of: Cancer science, 2020-05, Vol.111 (5), p.1452-1460
  • Description: Artificial intelligence (AI) has contributed substantially to the resolution of a variety of biomedical problems, including cancer, over the past decade. Deep learning, a subfield of AI that is highly flexible and supports automatic feature extraction, is increasingly being applied in various areas of both basic and clinical cancer research. In this review, we describe numerous recent examples of the application of AI in oncology, including cases in which deep learning has efficiently solved problems that were previously thought to be unsolvable, and we address obstacles that must be overcome before such application can become more widespread. We also highlight resources and datasets that can help harness the power of AI for cancer research. The development of innovative approaches to and applications of AI will yield important insights in oncology in the coming decade. Artificial intelligence (AI) has contributed substantially to the resolution of a variety of biomedical problems, including cancer, over the past decade. In this review, we describe numerous recent examples of the application of AI in oncology, including cases in which deep learning has efficiently solved problems that were previously thought to be unsolvable, and we address obstacles that must be overcome before such application can become more widespread.
  • Publisher: England: John Wiley & Sons, Inc
  • Language: English
  • Identifier: ISSN: 1347-9032
    EISSN: 1349-7006
    DOI: 10.1111/cas.14377
    PMID: 32133724
  • Source: Open Access: PubMed Central
    Open Access: Wiley Blackwell Open Access Journals
    AUTh Library subscriptions: ProQuest Central
    DOAJ Directory of Open Access Journals
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