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YAN Fangrong. Application and advance of artificial intelligence in biomedical field[J]. Journal of China Pharmaceutical University, 2023, 54(3): 263-268. DOI: 10.11665/j.issn.1000-5048.2023030304
Citation: YAN Fangrong. Application and advance of artificial intelligence in biomedical field[J]. Journal of China Pharmaceutical University, 2023, 54(3): 263-268. DOI: 10.11665/j.issn.1000-5048.2023030304
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Application and advance of artificial intelligence in biomedical field

  • Institute of Medical Big Data and Artificial Intelligence, School of Science, China Pharmaceutical University, Nanjing 211198, China

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  • Received Date: March 02, 2023
  • Revised Date: April 27, 2023
    Graphical Abstract
    • Abstract
  • Artificial intelligence (AI) has developed rapidly in the twentieth century, and has substantialy changed the modern way of life.At the same time, AI has greatly contributed to the development of the pharmaceutical industry, playing a key role in precision medicine, intelligent diagnosis, computer-aided drug design, and clinical trial decision-making, and has also greatly developed itself through its integration with the pharmaceutical industry.This paper outlines the key issues in research, describes the key applications of AI in the health and pharmaceutical industries, and finally analyzes the opportunities and challenges of AI in the health pharmaceutical industry to provide reference for the development of AI in the health and pharmaceutical fields.
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    • References (17)
  • [1]
    O'Sullivan S, Nevejans N, Allen C, et al. Legal, regulatory, and ethical frameworks for development of standards in artificial intelligence (AI) and autonomous robotic surgery[J]. Int J Med Robotics Comput Assist Surg, 2019, 15(1): e1968.
    [2]
    Sun YT, Selvarajan S, Zang ZL, et al. Protein classifier for thyroid nodules learned from rapidly acquired proteotypes[J]. medRxiv, 2020. doi: 10.1101/2020.04.09.20059741.
    [3]
    Clinton N, Patel K. The imprecise promise of the Precision Medicine Initiative (PMI): where we got it wrong and how can we fix it[J]? J Clin Oncol,2021,39(15_suppl):e15102.
    [4]
    Xu L, Li W, Sun XH, et al. Development trend of precision medicine in 2022[J]. Chin Bull Life Sci (生命科学), 2023, 35(1): 42-47.
    [5]
    Laguarta J, Hueto F, Subirana B. COVID-19 artificial intelligence diagnosis using only cough recordings[J]. IEEE Open J Eng Med Biol, 2020, 1: 275-281.
    [6]
    Wehbe RM, Sheng JY, Dutta S, et al. DeepCOVID-XR: an artificial intelligence algorithm to detect COVID-19 on chest radiographs trained and tested on a large U.S. clinical data set[J]. Radiology, 2021, 299(1): E167-E176.
    [7]
    Hashimoto N, Fukushima D, Koga R, et al. Multi-scale domain-adversarial multiple-instance CNN for cancer subtype classification with unannotated histopathological images[C]//2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). Seattle:IEEE,2020: 3851-3860.
    [8]
    Alom MZ, Yakopcic C, Hasan M, et al. Recurrent residual U-Net for medical image segmentation[J]. J Med Imag, 2019, 6(1): 1.
    [9]
    Toma?ev N, Glorot X, Rae JW, et al. A clinically applicable approach to continuous prediction of future acute kidney injury[J]. Nature, 2019, 572(7767): 116-119.
    [10]
    Weng SF, Reps J, Kai J, et al. Can machine-learning improve cardiovascular risk prediction using routine clinical data[J]? PLoS One, 2017, 12(4): e0174944.
    [11]
    Khan MTH, Fuskev?g OM, Sylte I. Discovery of potent thermolysin inhibitors using structure based virtual screening and binding assays[J]. J Med Chem, 2009, 52(1): 48-61.
    [12]
    Yasonik J. Multiobjective de novo drug design with recurrent neural networks and nondominated sorting[J]. J Cheminform, 2020, 12(1): 14.
    [13]
    Li XY, Xu YQ, Yao HQ, et al. Chemical space exploration based on recurrent neural networks: applications in discovering kinase inhibitors[J]. J Cheminform, 2020, 12(1): 42.
    [14]
    Winkler DA, Burden FR. Bayesian neural nets for modeling in drug discovery[J]. Drug Discov Today Biosilico, 2004, 2(3): 104-111.
    [15]
    Tunyasuvunakool K, Adler J, Wu Z, et al. Highly accurate protein structure prediction for the human proteome[J]. Nature, 2021, 596(7873): 590-596.
    [16]
    Ramamoorthy S, Murugan S. An attentive sequence model for adverse drug event extraction from biomedical text[J]. arXiv, 2018: 1801.00625.
    [17]
    Vaidya VP, Agrawal S, Sai Vinod M, et al. Development of an artificial intelligence model to dynamically predict metastatic recurrence of early-stage breast cancer patients[J]. J Clin Oncol, 2020, 38(15_suppl): e13078.
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