Department of Molecular and Cellular Biology, Medical Institute of Bioregulation, Kyushu University, Fukuoka, Japan.
Cancer Sci. 2020 May;111(5):1452-1460. doi: 10.1111/cas.14377. Epub 2020 Mar 21.
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.
在过去的十年中,人工智能(AI)在解决各种医学问题方面做出了重要贡献,包括癌症。深度学习作为 AI 的一个分支,具有很高的灵活性,支持自动特征提取,越来越多地应用于基础和临床癌症研究的各个领域。在这篇综述中,我们描述了人工智能在肿瘤学中的许多最新应用实例,包括深度学习高效解决了以前认为无法解决的问题的情况,并讨论了在更广泛应用之前必须克服的障碍。我们还强调了可以帮助利用人工智能为癌症研究提供动力的资源和数据集。未来十年,创新的人工智能方法和应用将为肿瘤学带来重要的研究进展。