Email Alert RSS
Volume 14 Issue 6
Nov.  2023
Turn off MathJax
Article Contents
Abstract
References
Related Articles
CHEN Youxin, XU Zhiyan. Artificial Intelligence Assisted Therapeutic Regimen and Technology Transformation in Retinal Diseases[J]. Medical Journal of Peking Union Medical College Hospital, 2023, 14(6): 1131-1134. DOI: 10.12290/xhyxzz.2023-0247
Citation: CHEN Youxin, XU Zhiyan. Artificial Intelligence Assisted Therapeutic Regimen and Technology Transformation in Retinal Diseases[J]. Medical Journal of Peking Union Medical College Hospital, 2023, 14(6): 1131-1134. DOI: 10.12290/xhyxzz.2023-0247
shu

Artificial Intelligence Assisted Therapeutic Regimen and Technology Transformation in Retinal Diseases

  • 1.

    Department of Ophthalmology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China

  • 2.

    Key Laboratory of Ocular Fundus Diseases, Chinese Academy of Medical Sciences, Beijing 100730, China

Funds: 

Capital's Funds for Health Improvement and Research Z191100007719002

AI+ Health Collaborative Innovation Cultivation Project Z221100003522026

AI+ Health Collaborative Innovation Cultivation Project Z211100003521020

National High Level Hospital Clinical Research Funding 2022-PUMCH-B-101

More Information
  • Corresponding author:

    CHEN Youxin, E-mail: chenyouxinpumch@163.com

  • Received Date: May 22, 2023
  • Accepted Date: October 16, 2023
  • Issue Publish Date: November 29, 2023
    Graphical Abstract
    • Abstract
  • In recent years, artificial intelligence (AI) technology has gradually penetrated into many medical specialties, bringing unprecedented changes to the medical field. At present, with the application of AI technology in the field of ophthalmology developing rapidly, AI diagnosis is rapid, highly accurate and objective, which can optimise the diagnosis and treatment mode of ophthalmology patients and greatly improve the efficiency of clinical diagnosis. Some AI ophthalmic imaging research has been translated into products, and therefore both domestic and international AI retinal imaging products are now available. However, due to various factors such as training data, R&D capability, clinical validation and market adaptation, many research outcomes still wait to to be translated. Therefore, we propose new therapeutic regimens of retinal diseases and analyze the underlying constraints to technology translation in AI research, with the hope of improving the use of AI technology in the diagnosis and treatment of fundus diseases.
    • FullText(HTML)
    • References (11)
  • [1]
    Curteanu S, Cartwright H. Neural networks applied in chemistry. Ⅰ. Determination of the optimal topology of multilayer perceptron neural networks[J]. J Chemometrics, 2011, 25: 527-549. DOI: 10.1002/cem.1401
    [2]
    Anton N, Doroftei B, Curteanu S, et al. Comprehensive Review on the Use of Artificial Intelligence in Ophthalmology and Future Research Directions[J]. Diagnostics (Basel), 2022, 13: 100. DOI: 10.3390/diagnostics13010100
    [3]
    Ting DSW, Pasquale LR, Peng L, et al. Artificial intelligence and deep learning in ophthalmology[J]. Br J Ophthalmol, 2019, 103: 167-175. DOI: 10.1136/bjophthalmol-2018-313173
    [4]
    明帅, 姚溪, 谢坤鹏, 等. 糖尿病视网膜病变人工智能自动诊断系统在社区和医院老年糖尿病患者中的应用效果分析[J]. 中华眼底病杂志, 2022, 38: 120-125.
    [5]
    Xu Z, Wang W, Yang J, et al. Automated diagnoses of age-related macular degeneration and polypoidal choroidal vasculopathy using bi-modal deep convolutional neural networks[J]. Br J Ophthalmol, 2021, 105: 561-566. DOI: 10.1136/bjophthalmol-2020-315817
    [6]
    Peng Y, Dharssi S, Chen Q, et al. DeepSeeNet: A Deep Learning Model for Automated Classification of Patient-based Age-related Macular Degeneration Severity from Color Fundus Photographs[J]. Ophthalmology, 2019, 126: 565-575. DOI: 10.1016/j.ophtha.2018.11.015
    [7]
    Burlina PM, Joshi N, Pacheco KD, et al. Use of Deep Learning for Detailed Severity Characterization and Estimation of 5-Year Risk Among Patients With Age-Related Macular Degeneration[J]. JAMA Ophthalmol, 2018, 136: 1359-1366. DOI: 10.1001/jamaophthalmol.2018.4118
    [8]
    Yoo TK, Kim SH, Kim M, et al. DeepPDT-Net: predicting the outcome of photodynamic therapy for chronic central serous chorioretinopathy using two-stage multimodal transfer learning[J]. Sci Rep, 2022, 12: 18689. DOI: 10.1038/s41598-022-22984-6
    [9]
    Xu F, Yu X, Gao Y, et al. Predicting OCT images of short-term response to anti-VEGF treatment for retinal vein occlusion using generative adversarial network[J]. Front Bioeng Biotechnol, 2022, 10: 914964. DOI: 10.3389/fbioe.2022.914964
    [10]
    Oh R, Lee EK, Bae K, et al. Deep Learning-based Prediction of Axial Length Using Ultra-widefield Fundus Photography[J]. Korean J Ophthalmol, 2023, 37: 95-104. DOI: 10.3341/kjo.2022.0059
    [11]
    Niu Y, Gu L, Zhao Y, et al. Explainable Diabetic Retinopathy Detection and Retinal Image Generation[J]. IEEE J Biomed Health Inform, 2022, 26: 44-55. DOI: 10.1109/JBHI.2021.3110593
    • Related Articles

  • Related Articles

    [1]LI Chaofan, LIU Conghui, SUN Mingyang, WU Lin. Comparative Analysis of "Same Disease, Same Price" Policy in Diagnosis Related Group Payment Under the Goal of Tiered Healthcare Delivery[J]. Medical Journal of Peking Union Medical College Hospital, 2024, 15(5): 1045-1051. DOI: 10.12290/xhyxzz.2024-0414
    [2]LI Yang, DU Leilei, XU Fei, LI Yixuan, QIAO En. Big Data and Artificial Intelligence in Medicine[J]. Medical Journal of Peking Union Medical College Hospital, 2023, 14(1): 184-189. DOI: 10.12290/xhyxzz.2022-0182
    [3]Multi-disciplinary Expert Team for Primary Care COVID-19 Practice, Peking Union Medical College Hospital. Practical Recommendations of Peking Union Medical College Hospital for Assessment and Management of COVID-19 in Primary Care (2023)[J]. Medical Journal of Peking Union Medical College Hospital, 2023, 14(1): 60-74. DOI: 10.12290/xhyxzz.2023-0014
    [4]WANG Feiyue. Digital Doctors and Parallel Healthcare: From Medical Knowledge Automation to Intelligent Metasystems Medicine[J]. Medical Journal of Peking Union Medical College Hospital, 2021, 12(6): 829-833. DOI: 10.12290/xhyxzz.2021-0586
    [5]Zhu-ming JIANG, Zhuo LI, Yang WANG, Hui ZHANG, Yan WANG, Bin JIE, Hai FANG, Wei LI, Yan-wu ZHANG, Fen ZHANG, Tie-jun HU, Da-kui LI, Wei-ming KANG, Kang YU, Xin YE. Brief Review of the 3T's Roadmap of Translational Medicine for Parenteral and Enteral Nutrition in China[J]. Medical Journal of Peking Union Medical College Hospital, 2020, 11(5): 508-513. DOI: 10.3969/j.issn.1674-9081.2020.05.002
    [6]Rui-feng LIU, Yu XIA, Yu-xin JIANG. Application of Artificial Intelligence in Ultrasound Medicine[J]. Medical Journal of Peking Union Medical College Hospital, 2018, 9(5): 453-457. DOI: 10.3969/j.issn.1674-9081.2018.05.015

  • Cited by

    Periodical cited type(8)

    1. 毕建蕾，李亚，陆俊玲，王馨犹，刘佳欣，李雪，王丽霞. 新医科背景下“医学+X”模式在妇产科学研究生教学中的运用. 医学教育研究与实践. 2025(01): 34-40 .
    2. 戴佳原，须晋，谢静，沈敏，张抒扬. 罕见病医学科临床医学博士后教学模式探索. 协和医学杂志. 2024(05): 1224-1229 . 本站查看
    3. 蔡晗. 专科医院博士后人才引育与激励机制研究. 中国卫生产业. 2024(06): 41-44 .
    4. 张佳慧，丁欣，崔娜. 分层培养模式在重症医学科进修医师教学实践中的探索. 医学研究杂志. 2023(04): 185-188 .
    5. 龚梦，雷凡. 以住培学员为中心的临床教学的思考. 继续医学教育. 2023(06): 113-116 .
    6. 张翰林，何紫棠，李玥，罗林枝，张抒扬. 临床医师胜任力的经典模型与研究进展. 协和医学杂志. 2023(06): 1296-1300 . 本站查看
    7. 蒋邦红，张莉，宋培军，徐静，李旭文，陈卫东. 分层递进式教学法对整形外科住培医师面部创伤教学的效果评价. 淮海医药. 2022(01): 95-98 .
    8. 张菁，芮娜，冉红，张平洋. 模拟器教学在临床医学技能培训中的应用与思考. 中国医药导报. 2022(35): 189-192 .

    Other cited types(1)

Catalog

    Get Citation
    PDF
    XML

    Article Metrics

    Article views (733) PDF downloads (113) Cited by(9)
    Related
    Links: National Health Commission of the People's Republic of China Chinese Academy of Medical Sciences(CAMS) AMLC Check CNKI Database CNKI Term Online Chinese General Practice
    Address：Room 302,Third Floor,Building 7, No. 1 Shuaifuyuan, Wangfujing, Dongcheng District, Beijing 100730, China
    Tel：010-69154261/4262
    E - mail：medj@pumch.cn mjpumch@126.com
    Copyright of website：Editorial Office of Medical Journal of Peking Union Medical College Hospital

    Supported by: Beijing Renhe Information Technology Co., Ltd.  Baidu Analytics

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return
    x Close Forever Close