Volume 19 Issue 9
Sep.  2021
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Article Navigation >  Chinese Journal of General Practice  > 2021  >  19(9): 1433-1436,1572
YUAN Bo, DAI Hua, WU Jia, FU Wen-jun, WEN Juan, ZHAO Qian. Application of artificial intelligence applications in general practice[J]. Chinese Journal of General Practice, 2021, 19(9): 1433-1436,1572. doi: 10.16766/j.cnki.issn.1674-4152.002079
Citation: YUAN Bo, DAI Hua, WU Jia, FU Wen-jun, WEN Juan, ZHAO Qian. Application of artificial intelligence applications in general practice[J]. Chinese Journal of General Practice, 2021, 19(9): 1433-1436,1572. doi: 10.16766/j.cnki.issn.1674-4152.002079
shu

Application of artificial intelligence applications in general practice

doi: 10.16766/j.cnki.issn.1674-4152.002079

  • International Medical Center, General Practice Unit, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China

Funds:

 2021YFG0329

 2020YJ0287

 2019-RK00-00221-ZF

 ZH2020-104

 2019004

  • Received Date: 2021-07-02
    Available Online: 2022-02-15
    Abstract
  • Artificial intelligence (AI) has entered a period of vigorous development although it has only 65 years since its inception. AI technology is currently widely used in finance, medical care, security, transportation, education, autonomous driving, and so on. In recent years, the concepts of 'big health', cloud computing, and medical big data have frequently appeared in the world, which have also promoted the accelerated development of AI in the medical field, such as electronic medical records, medical image recognition, disease risk prediction, health management, auxiliary diagnosis, and drug research. In 2017, the State Council issued the "New Generation AI Development Plan", which proposed to promote the application of new models and new methods of AI treatment, and establish a fast and precision medical system. Intelligent medical has received extremely high attention, and it is predicted that intelligent medical will account for 1/5 of the overall AI. Since the late 1980s, under the vigorous promotion of the government, general practice (GP) has been formally established and has achieved considerable development in China. In 2011, the State Council issued the "Guiding Opinions on Establishing a General Practitioner regime", and the GP has entered a rapid pace. In the development stage, the GP service model is gradually promoted at the grassroots level. In 2018, the State Council issued the "Opinions on Promoting the Development of ' Internet +' medical health", which proposed to explore the construction of intelligent health management and intelligent elderly community service system, optimize and promote "Internet +" family doctor contract, education and popular science services. This article summarizes the application and development status of AI in GP as follows, GP service, family doctor contract, grading diagnosis and treatment, general practitioner training, and community public health services, and also analyzes the current challenges, and finally look forward to the future development prospects.

     

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    • References(37)
  • [1]
    德勤科技.2021全球人工智能发展白皮书[R]. 上海:德勤科技, 2019.
    [2]
    中国电子技术标准化研究院.人工智能标准化白皮书(2018版)[R]. 2018.
    [3]
    于晓松.新中国成立70年以来中国全科医学发展与展望[J]. 中华全科医学, 2019, 17(11):1797-1799. https://www.cnki.com.cn/Article/CJFDTOTAL-SYQY201911001.htm
    [4]
    ENSHAEI A, ROBSON C N, EDMONDSON R J.Artificial intelligence systems as prognostic and predictive tools in ovarian cancer[J]. Ann Surg Oncol, 2015, 22(12):3970-3975. doi: 10.1245/s10434-015-4475-6
    [5]
    GOLDEN J A.Deep learning algorithms for detection of lymph node metastases from breast cancer:Helping artificial intelligence be seen[J]. JAMA, 2017, 318(22):2184-2186. doi: 10.1001/jama.2017.14580
    [6]
    GULSHAN V, PENG L, CORAM M, et al.Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs[J]. JAMA, 2016, 316(22):2402-2410. doi: 10.1001/jama.2016.17216
    [7]
    XU Y M, ZHANG T, XU H, et al.Deep learning in CT images:Automated pulmonary nodule detection for subsequent management using convolutional neural network[J]. Cancer Manag Res, 2020, 12:2979-2992. doi: 10.2147/CMAR.S239927
    [8]
    SHEN J, ZHANG C, JIANG B, et al.Artificial intelligence versus clinicians in disease diagnosis:Systematic review[J]. JMIR Med Inform, 2019, 7(3):e10010. doi: 10.2196/10010
    [9]
    杨柯, 汪志涛.人工智能赋能下的社区居家养老服务模式构建研究[J]. 云南行政学院学报, 2020, 22(3):145-152. doi: 10.3969/j.issn.1671-0681.2020.03.021
    [10]
    WALLIS C.How artificial intelligence will change medicine[J]. Nature, 2019, 576(7787):S48. doi: 10.1038/d41586-019-03845-1
    [11]
    BUTOW P, HOQUE E.Using artificial intelligence to analyse and teach communication in healthcare[J]. Breast, 2020, 50:49-55. doi: 10.1016/j.breast.2020.01.008
    [12]
    上海交通大学人工智能研究院.中国人工智能医疗白皮书[R]. 2019.
    [13]
    BRISIMI T S, XU T, WANG T, et al.Predicting chronic disease hospitalizations from electronic health records: An interpretable classification approach[J]. Proc IEEE Inst Electr Electron Eng, 2018, 106(4):690-707. doi: 10.1109/JPROC.2017.2789319
    [14]
    YU K H, BEAM A L, KOHANE I S.Artificial intelligence in healthcare[J]. Nat Biomed Eng, 2018, 2(10):719-731. doi: 10.1038/s41551-018-0305-z
    [15]
    DESAI A N.Artificial Intelligence:Promise, pitfalls, and perspective[J]. JAMA, 2020, 323(24):2448-2449. doi: 10.1001/jama.2020.8737
    [16]
    RUBIN R.Obstacles to implementing AI tools in health care[J]. JAMA, 2021, 325(4):333.
    [17]
    MINTZ Y, BRODIE R.Introduction to artificial intelligence in medicine[J]. Minim Invasive Ther Allied Technol, 2019, 28(2):73-81. doi: 10.1080/13645706.2019.1575882
    [18]
    胡智博.人工智能在医学领域应用的现状与展望[J]. 电子元器件与信息技术, 2020, 4(12):61-62. https://www.cnki.com.cn/Article/CJFDTOTAL-DYXU202012030.htm
    [19]
    HOSNY A, PARMAR C, QUACKENBUSH J, et al.Artificial intelligence in radiology[J]. Nat Rev Cancer, 2018, 18(8):500-510. doi: 10.1038/s41568-018-0016-5
    [20]
    ZAKHEM G A, MOTOSKO C C, HO R S.How should artificial intelligence screen for skin cancer and deliver diagnostic predictions to patients?[J]. JAMA Dermatol, 2018, 154(12):1383-1384. doi: 10.1001/jamadermatol.2018.2714
    [21]
    SUMMERTON N, CANSDALE M.Artificial intelligence and diagnosis in general practice[J]. Br J Gen Pract, 2019, 69(684):324-325. doi: 10.3399/bjgp19X704165
    [22]
    ZHOU M, WANG H, ZENG X, et al.Mortality, morbidity, and risk factors in China and its provinces, 1990-2017:A systematic analysis for the Global Burden of Disease Study 2017[J]. Lancet, 2019, 394(10204):1145-1158. doi: 10.1016/S0140-6736(19)30427-1
    [23]
    崔骥, 许家佗.人工智能背景下中医诊疗技术的应用与展望[J]. 第二军医大学学报, 2018, 39(8):846-851. https://www.cnki.com.cn/Article/CJFDTOTAL-DEJD201808010.htm
    [24]
    GUO Y, REN X, CHEN Y X, et al Artificial intelligence meets Chinese medicine[J]. Chin J Integr Med, 2019, 25(9):648-653. doi: 10.1007/s11655-019-3169-5
    [25]
    MORTAZAVI B J, BUCHOLZ E M, DESAI N R, et al.Comparison of machine learning methods with national cardiovascular data registry models for prediction of risk of bleeding after percutaneous coronary intervention[J]. JAMA Netw Open, 2019, 2(7):e196835. doi: 10.1001/jamanetworkopen.2019.6835
    [26]
    CHEN T, LI X, LI Y, et al.Prediction and risk stratification of kidney outcomes in IgA nephropathy[J]. Am J Kidney Dis, 2019, 74(3):300-309. doi: 10.1053/j.ajkd.2019.02.016
    [27]
    陈国湘, 李俊, 韦华, 等.基于人工智能技术的全科医生培养模式探索[J]. 中华全科医学, 2021, 19(2):167-170. https://www.cnki.com.cn/Article/CJFDTOTAL-SYQY202102001.htm
    [28]
    邢珍珍.人工智能赋能下社区智慧养老服务模式及关键技术研究[J]. 护理研究, 2021, 35(9):1573-1579. https://www.cnki.com.cn/Article/CJFDTOTAL-SXHZ202109013.htm
    [29]
    郝晓宁, 马骋宇, 刘志业, 等.医患双方对基层医疗卫生信息化建设的满意度研究[J]. 卫生经济研究, 2020, 37(7):6-9. https://www.cnki.com.cn/Article/CJFDTOTAL-WSJJ202007003.htm
    [30]
    陈国湘, 李俊, 韦华, 等.基于人工智能技术的全科医生培养模式探索[J]. 中华全科医学, 2021, 19(2):167-170. https://www.cnki.com.cn/Article/CJFDTOTAL-SYQY202102001.htm
    [31]
    樊荣荣, 施晓雷, 孙安, 等.人工智能在住院医师规范化培养中的应用价值探讨[J]. 肿瘤影像学, 2018, 27(4):261-264. https://www.cnki.com.cn/Article/CJFDTOTAL-YXYX201804004.htm
    [32]
    SIM S, CHO M.Convergence model of AI and IoT for virus disease control system[J]. Pers Ubiquitous Comput, 2021.DOI: 10.1007/s00779-021-01577-6.
    [33]
    欧阳丽炜, 袁勇, 郑心湖, 等.基于区块链的传染病监测与预警技术[J]. 智能科学与技术学报, 2020, 2(2):135-143. https://www.cnki.com.cn/Article/CJFDTOTAL-ZNJS202002005.htm
    [34]
    耿相珍, 曹银杰.基于人工智能的社区矫正定位系统[J]. 现代计算机, 2020(12):48-51. https://www.cnki.com.cn/Article/CJFDTOTAL-XDJS202012009.htm
    [35]
    LI X, KRUMHOLZ H M, YIP W, et al.Quality of primary health care in China:Challenges and recommendations[J]. Lancet, 2020, 395(10239):1802-1812. doi: 10.1016/S0140-6736(20)30122-7
    [36]
    HOPCROFT K.Artificial intelligence may not recognise the nuances of general practice[J]. BMJ, 2018, 363:k5205. http://www.ncbi.nlm.nih.gov/pubmed/30563916
    [37]
    Anticipating artificial intelligence[J]. Nature, 2016, 532(7600):413.
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