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Cancer Innovation 2022, 1(1): 80-91 https://doi.org/10.1002/cai2.9
Review | Open Access | Issue | Published: 15 June 2022

Application of informatics in cancer research and clinical practice: Opportunities and challenges

Show Author's Information Na Hong1,  Gang Sun2,  Xiuran Zuo3,  Meng Chen4,  Li Liu5,  Jiani Wang4,  Xiaobin Feng6,  Wenzhao Shi1,  Mengchun Gong1,7 ( ),  Pengcheng Ma5 ( )
Department of Medical Sciences, Digital Health China Technologies Co., Ltd., Beijing, China
Xinjiang Cancer Center, Key Laboratory of Oncology of Xinjiang Uyghur Autonomous Region, The Affiliated Cancer Hospital of Xinjiang Medical University, Ürümqi, China
Department of Information, Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
Big Data Center, Nanfang Hospital, Southern Medical University, Guangzhou, China
Hepato‐Pancreato‐Biliary Center, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing, China
Institute of Health Management, Southern Medical University, Guangzhou, China
Keywords:
machine learning, artificial intelligence application, cancer informatics
Cite this article:
Hong N, Sun G, Zuo X, et al. Application of informatics in cancer research and clinical practice: Opportunities and challenges. Cancer Innovation, 2022, 1(1): 80-91. https://doi.org/10.1002/cai2.9
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Abstract Full text About this article

Cancer informatics has significantly progressed in the big data era. We summarize the application of informatics approaches to the cancer domain from both the informatics perspective (e.g., data management and data science) and the clinical perspective (e.g., cancer screening, risk assessment, diagnosis, treatment, and prognosis). We discuss various informatics methods and tools that are widely applied in cancer research and practices, such as cancer databases, data standards, terminologies, high‐throughput omics data mining, machine‐learning algorithms, artificial intelligence imaging, and intelligent radiation. We also address the informatics challenges within the cancer field that pursue better treatment decisions and patient outcomes, and focus on how informatics can provide opportunities for cancer research and practices. Finally, we conclude that the interdisciplinary nature of cancer informatics and collaborations are major drivers for future research and applications in clinical practices. It is hoped that this review is instrumental for cancer researchers and clinicians with its informatics‐specific insights.


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About this article

Application of informatics in cancer research and clinical practice: Opportunities and challenges

Show Author's information Na Hong1, Gang Sun2, Xiuran Zuo3, Meng Chen4, Li Liu5, Jiani Wang4, Xiaobin Feng6, Wenzhao Shi1, Mengchun Gong1,7 ( ), Pengcheng Ma5 ( )
Department of Medical Sciences, Digital Health China Technologies Co., Ltd., Beijing, China
Xinjiang Cancer Center, Key Laboratory of Oncology of Xinjiang Uyghur Autonomous Region, The Affiliated Cancer Hospital of Xinjiang Medical University, Ürümqi, China
Department of Information, Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
Big Data Center, Nanfang Hospital, Southern Medical University, Guangzhou, China
Hepato‐Pancreato‐Biliary Center, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing, China
Institute of Health Management, Southern Medical University, Guangzhou, China

Abstract

Cancer informatics has significantly progressed in the big data era. We summarize the application of informatics approaches to the cancer domain from both the informatics perspective (e.g., data management and data science) and the clinical perspective (e.g., cancer screening, risk assessment, diagnosis, treatment, and prognosis). We discuss various informatics methods and tools that are widely applied in cancer research and practices, such as cancer databases, data standards, terminologies, high‐throughput omics data mining, machine‐learning algorithms, artificial intelligence imaging, and intelligent radiation. We also address the informatics challenges within the cancer field that pursue better treatment decisions and patient outcomes, and focus on how informatics can provide opportunities for cancer research and practices. Finally, we conclude that the interdisciplinary nature of cancer informatics and collaborations are major drivers for future research and applications in clinical practices. It is hoped that this review is instrumental for cancer researchers and clinicians with its informatics‐specific insights.

Keywords: machine learning, artificial intelligence application, cancer informatics

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Received: 13 April 2022
Accepted: 24 April 2022
Published: 15 June 2022
Issue date: June 2022

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© 2022 The Authors.

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We thank Chao Liu, Ge Wu, Xiaoyu Wu, Yuanshi Jiao, and Yunchuan Qiao for their literature collection and review support. 

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