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Review
. 2021 Nov;41(11):1100-1115.
doi: 10.1002/cac2.12215. Epub 2021 Oct 6.

Artificial intelligence for assisting cancer diagnosis and treatment in the era of precision medicine

Zi-Hang Chen  1   2 , Li Lin  1 , Chen-Fei Wu  1 , Chao-Feng Li  3 , Rui-Hua Xu  4 , Ying Sun  1
Affiliations
Review

Artificial intelligence for assisting cancer diagnosis and treatment in the era of precision medicine

Zi-Hang Chen et al. Cancer Commun (Lond). 2021 Nov.

Abstract

Over the past decade, artificial intelligence (AI) has contributed substantially to the resolution of various medical problems, including cancer. Deep learning (DL), a subfield of AI, is characterized by its ability to perform automated feature extraction and has great power in the assimilation and evaluation of large amounts of complicated data. On the basis of a large quantity of medical data and novel computational technologies, AI, especially DL, has been applied in various aspects of oncology research and has the potential to enhance cancer diagnosis and treatment. These applications range from early cancer detection, diagnosis, classification and grading, molecular characterization of tumors, prediction of patient outcomes and treatment responses, personalized treatment, automatic radiotherapy workflows, novel anti-cancer drug discovery, and clinical trials. In this review, we introduced the general principle of AI, summarized major areas of its application for cancer diagnosis and treatment, and discussed its future directions and remaining challenges. As the adoption of AI in clinical use is increasing, we anticipate the arrival of AI-powered cancer care.

Keywords: artificial intelligence; cancer diagnosis; cancer research; cancer treatment; convolutional neural network; deep learning; deep neural network; oncology.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

FIGURE 1
FIGURE 1
The relationship between artificial intelligence, machine learning, and deep learning and commonly used algorithms as examples. CNN, convolutional neural network
FIGURE 2
FIGURE 2
Publication statistics of deep learning by cancer area over the past five years, searched on PubMed. A. Publication statistics of deep learning by cancer diagnosis, precision medicine, radiotherapy, and cancer research. B. Publication statistics of deep learning for different cancer sites
FIGURE 3
FIGURE 3
Applications of AI in cancer diagnosis, treatment and research. OARs, organs at risk
See this image and copyright information in PMC

References

    1. McCarthy J, Minsky ML, Rochester N, Shannon CE. A proposal for the dartmouth summer research project on artificial intelligence, august 31, 1955. AI Magazine. 2006;27(4):12.
    1. Yasser E‐M, Honavar V, Hall A. Artificial Intelligence Research Laboratory. 2005.
    1. Yu KH, Beam AL, Kohane IS. Artificial intelligence in healthcare. Nat Biomed Eng. 2018;2(10):719–31. - PubMed
    1. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2020. CA Cancer J Clin. 2020;70(1):7–30. - PubMed
    1. Wainberg M, Merico D, Delong A, Frey BJ. Deep learning in biomedicine. Nat Biotechnol. 2018;36(9):829–38. - PubMed