Artificial intelligence in clinical research of cancers.

Journal: Briefings in bioinformatics
Published Date:

Abstract

Several factors, including advances in computational algorithms, the availability of high-performance computing hardware, and the assembly of large community-based databases, have led to the extensive application of Artificial Intelligence (AI) in the biomedical domain for nearly 20 years. AI algorithms have attained expert-level performance in cancer research. However, only a few AI-based applications have been approved for use in the real world. Whether AI will eventually be capable of replacing medical experts has been a hot topic. In this article, we first summarize the cancer research status using AI in the past two decades, including the consensus on the procedure of AI based on an ideal paradigm and current efforts of the expertise and domain knowledge. Next, the available data of AI process in the biomedical domain are surveyed. Then, we review the methods and applications of AI in cancer clinical research categorized by the data types including radiographic imaging, cancer genome, medical records, drug information and biomedical literatures. At last, we discuss challenges in moving AI from theoretical research to real-world cancer research applications and the perspectives toward the future realization of AI participating cancer treatment.

Authors

  • Dan Shao
    Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education, College of Computer Science and Technology, Jilin University, Changchun 130012, China.
  • Yinfei Dai
    College of Computer Science and Technology, Key Laboratory of Human Health Status Identification and Function Enhancement of Jilin Province, Changchun University, Changchun 130022, China.
  • Nianfeng Li
    College of Computer Science and Technology, Key Laboratory of Human Health Status Identification and Function Enhancement of Jilin Province, Changchun University, Changchun 130022, China.
  • Xuqing Cao
    Department of Neurology, People's Hospital of Ningxia Hui Autonomous Region (The Affiliated people's Hospital of Ningxia Medical University and The First Affiliated Hospital of Northwest Minzu University), Yinchuan 750002, China.
  • Wei Zhao
    Key Laboratory of Synthetic and Biological Colloids, Ministry of Education, Jiangnan University, Wuxi 214122, Jiangsu Province, P. R. China. lxy@jiangnan.edu.cn zhuye@jiangnan.edu.cn.
  • Li Cheng
  • Zhuqing Rong
    School of Science, Key Laboratory of Human Health Status Identification and Function Enhancement of Jilin Province, Changchun University, Changchun 130022, China.
  • Lan Huang
  • Yan Wang
    College of Animal Science and Technology, Beijing University of Agriculture, Beijing, China.
  • Jing Zhao
    Department of Pharmacy, Pharmacoepidemiology and Drug Safety Research Group, Faculty of Mathematics and Natural Sciences, University of Oslo, Oslo, Norway.