Advances in the application of AI in chronic disease management in primary care

HU Jiamin; QIU Yan; REN Jingjing

doi:10.16766/j.cnki.issn.1674-4152.003431

Volume 22 Issue 3

Mar. 2024

Turn off MathJax

Article Contents

Article Navigation > Chinese Journal of General Practice > 2024 > 22(3): 481-485

HU Jiamin, QIU Yan, REN Jingjing. Advances in the application of AI in chronic disease management in primary care[J]. Chinese Journal of General Practice, 2024, 22(3): 481-485. doi: 10.16766/j.cnki.issn.1674-4152.003431

Citation:

HU Jiamin, QIU Yan, REN Jingjing. Advances in the application of AI in chronic disease management in primary care[J]. Chinese Journal of General Practice, 2024, 22(3): 481-485. doi: 10.16766/j.cnki.issn.1674-4152.003431

Citation:

PDF( 493 KB)

Advances in the application of AI in chronic disease management in primary care

doi: 10.16766/j.cnki.issn.1674-4152.003431

HU Jiamin¹
, QIU Yan¹
, REN Jingjing^{1
,
,}

1.
Department of General Practice, the First Affiliated Hospital, Zhejiang University school of Medicine, Hangzhou, Zhejiang 310003, China

Funds:

72274169

Received Date: 2023-03-28
Available Online: 2024-05-27

Abstract

Abstract

In the current healthcare sector, the integration of artificial intelligence (AI) technology has opened new avenues for improving the efficiency and quality of chronic disease management. Especially within primary healthcare systems, the application of AI is gradually transitioning from theory to practice, supporting general practitioners in better responding to patient needs and providing personalized and efficient medical services. In the field of chronic disease management, the involvement of AI has made the comprehensive management of chronic diseases more intelligent, enhancing the accuracy of prevention, diagnosis, and treatment. The role of general practitioners, with the aid of AI, is also undergoing a transformation; they are no longer simply the executors of diagnosis and treatment, but have become integrators of medical resources and guides for patient health management. AI can provide personalized rehabilitation treatment plans based on patients ' conditions and needs. Intelligent technology can be used to continuously monitor patients ' vital signs and changes in their condition, alerting potential health risks. AI can also assist patients in improving their lifestyle habits, such as by using smart reminders and behavioral guidance to help patients maintain a reasonable diet and exercise. AI can build local health education knowledge bases, popularizing knowledge and management skills for chronic diseases. However, the limitations of information technology may lead to insufficient data processing capabilities and service coverage. Security and privacy issues require strict compliance with relevant laws and regulations to ensure protection. Moreover, over-reliance on AI technology may overlook the human care and direct communication between doctors and patients. In the future, by strengthening the understanding and mastery of AI technology among primary healthcare workers, and by increasing the public ' s awareness and acceptance of AI technology, we can promote the deep application of AI in grassroots chronic disease management, making a positive contribution to improving the health level of the entire population.
- Artificial intelligence,
- Primary health care,
- Chronic disease management,
- General practitioners

FullText(HTML)

References(36)

References

[1]	国家卫生健康委员会, 国家中医药管理局. 进一步改善护理服务行动计划(2023—2025年)[J]. 中国护理管理, 2023, 23(7): 961-963. doi: 10.3969/j.issn.1672-1756.2023.07.001
[2]	彭婉琳, 陈德凤, 李蓓, 等. ChatGPT人工智能语言机器人在护理领域应用现状与展望[J]. 全科护理, 2023, 21(35): 4934-4937. doi: 10.12104/j.issn.1674-4748.2023.35.008
[3]	姚泽阳, 谢稳, 邱海龙, 等. 人工智能在临床医学中的应用与展望[J]. 医学信息学杂志, 2020, 41(3): 39-43. doi: 10.3969/j.issn.1673-6036.2020.03.009
[4]	VAIDYAM A N, WISNIEWSKI H, HALAMKA J D, et al. Chatbots and conversational agents in mental health: a review of the psychiatric landscape[J]. Can J Psychiatry, 2019, 64(7): 456-464. doi: 10.1177/0706743719828977
[5]	程洁, 张潇潭, 王哲, 等. 我国全科医生队伍建设地区差异研究[J]. 中国医院, 2023, 27(6): 62-65. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGYU202306017.htm
[6]	以经济高质量发展促中国式现代化推进: 北京大学经济学院专家学者议两会论点精选(2023年)[J]. 经济研究参考, 2023(4): 26-52.
[7]	郭怡琳, 于娜. AI医疗新趋势[N]. 华夏时报, 2023-05-22(013): 1-2.
[8]	国家统计局. 第七次全国人口普查公告解读. (2021-05-12)[2023-01-22]. http://www.stats.gov.cn/xxgk/jd/sjjd2020/202105/t20210512_1817342.html.
[9]	郑欣雅, 黄运有, 张奕婷, 等. 医学人工智能标准体系: 历史与现状[J]. 协和医学杂志, 2023, 14(6): 1135-1141. https://www.cnki.com.cn/Article/CJFDTOTAL-XHYX202306003.htm
[10]	SCERRI A, MORIN K H. Using chatbots like ChatGPT to support nursing practice[J]. J Clin Nurs, 2023, 32(15-16): 4211-4213. doi: 10.1111/jocn.16677
[11]	HUANG J T, YEUNG A M, KERR D, et al. Using ChatGPT to predict the future of diabetes technology[J]. J Diabetes Sci Technol, 2023, 17(3): 853-854. doi: 10.1177/19322968231161095
[12]	PENG M L, WICKERSHAM J A, ALTICE F L, et al. Formative evaluation of the acceptance of HIV prevention artificial intelligence chatbots by men who have sex with men in malaysia: focus group study[J]. JMIR Form Res, 2022, 6(10): e42055. DOI: 10.2196/42055.
[13]	李献青, 张玲. 公共健康视域下全科医生健康管理与指导能力的培养[J]. 保健医学研究与实践, 2020, 17(4): 77-81. https://www.cnki.com.cn/Article/CJFDTOTAL-GXBJ202004018.htm
[14]	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. doi: 10.16766/j.cnki.issn.1674-4152.001758
[15]	RANZANI R, LAMBERCY O, METZGER J C, et al. Neurocognitive robot-assisted rehabilitation of hand function: a randomized control trial on motor recovery in subacute stroke[J]. J Neuroeng Rehabil, 2020, 17(1): 115. doi: 10.1186/s12984-020-00746-7
[16]	KILBRIDE C, WARLAND A, STEWART V, et al. Rehabilitation using virtual gaming for hospital and home-based training for the upper limb post stroke (RHOMBUS Ⅱ): protocol of a feasibility randomised controlled trial[J]. BMJ Open, 2022, 12(6): e058905. DOI: 10.1136/bmjopen-2021-058905.
[17]	DE LUCA R, MAGGIO M G, MARESCA G, et al. Improving cognitive function after traumatic brain injury: a clinical trial on the potential use of the semi-immersive virtual reality[J]. Behav Neurol, 2019: 9268179. DOI: 10.1155/2019/9268179.
[18]	HU X, CHEN W Z, BAI Y Y, et al. Establishment of a diagnostic model of coronary heart disease in elderly patients with diabetes mellitus based on machine learning algorithms[J]. J Geriatr Cardiol, 2022, 19(6): 445-455.
[19]	VANEGAS E, IGUAL R, PLAZA I. Sensing systems for respiration monitoring: a technical systematic review[J]. Sensors (Basel), 2020, 20(18): 5446. doi: 10.3390/s20185446
[20]	MUKHERJEE D, DHAR K, SCHWENKER F, et al. Ensemble of deep learning models for sleep apnea detection: an experimental study[J]. Sensors(Basel), 2021, 21(16): 5425.
[21]	吕煜焱, 丁思霄, 赵逸凡, 等. 人工智能化的远程心电监测在心血管疾病中的应用[J]. 中国心血管杂志, 2020, 25(3): 270-273. doi: 10.3969/j.issn.1007-5410.2020.03.014
[22]	CHATTERJEE A, GERDES M W, MARTINEZ S G. Identification of risk factors associated with obesity and overweight: a machine learning overview[J]. Sensors (Basel), 2020, 20(9): 2734. doi: 10.3390/s20092734
[23]	KURT B, KIKRBR L B. Clinical decision support system for early diagnosis of heart attack using machine learning methods[J]. Eskişehir Technical University Journal of Science and Technology A - Applied Sciences and Engineering, 2023. DOI: 10.18038/estubtda.1025092.
[24]	FARUQUI S H A, DU Y, MEKA R, et al. Development of a deep learning model for dynamic forecasting of blood glucose level for type 2 diabetes mellitus: secondary analysis of a randomized controlled trial[J]. JMIR Mhealth Uhealth, 2019, 7(11): e14452. DOI: 10.2196/14452.
[25]	GOLDENHERSCH E, THRUL J, UNGARETTI J, et al. Virtual reality smartphone-based intervention for smoking cessation: pilot randomized controlled trial on initial clinical efficacy and adherence[J]. J Med Internet Res, 2020, 22(7): e17571. DOI: 10.2196/17571.
[26]	何金超, 罗芳, 袁知才, 等. 协同过滤和粒子群算法在饮食推荐中的应用[J]. 计算机应用与软件, 2019, 36(8): 36-40, 59. doi: 10.3969/j.issn.1000-386x.2019.08.007
[27]	HAMAN M, ŠKOLNÍK M. Using ChatGPT to conduct a literature review[J]. Account Res, 2023: 1-3.
[28]	KOLECK T A, DREISBACH C, BOURNE P E, et al. Natural language processing of symptoms documented in free-text narratives of electronic health records: a systematic review[J]. J Am Med Inform Assoc, 2019, 26(4): 364-379. doi: 10.1093/jamia/ocy173
[29]	ODOM-FORREN J. The role of ChatGPT in perianesthesia nursing[J]. J Perianesth Nurs, 2023, 38(2): 176-177. doi: 10.1016/j.jopan.2023.02.006
[30]	LI J, HUANG J, ZHENG L B, et al. Application of artificial intelligence in diabetes education and management: present status and promising prospect[J]. Front Public Health, 2020, 8: 173. doi: 10.3389/fpubh.2020.00173
[31]	唐晓波, 郑杜, 谭明亮. 慢性病健康教育知识服务系统模型构建研究[J]. 情报科学, 2019, 37(1): 134-140. https://www.cnki.com.cn/Article/CJFDTOTAL-QBKX201901021.htm
[32]	黄水晶. 基层医疗机构基本公共卫生资金管理存在的问题及对策研究[J]. 活力, 2023, 41(17): 145-147. https://www.cnki.com.cn/Article/CJFDTOTAL-HLYT202317048.htm
[33]	徐雪芬, 王红燕, 郭萍萍, 等. 人工智能在慢性病患者健康管理中的应用进展[J]. 中华护理杂志, 2023, 58(9): 1063-1067. doi: 10.3761/j.issn.0254-1769.2023.09.006
[34]	PARVIAINEN J, RANTALA J. Chatbot breakthrough in the 2020s? An ethical reflection on the trend of automated consultations in health care[J]. Med Health Care Philos, 2021, 25(1): 61-71.
[35]	BELTRAMI E J, GRANTKELS J M. Consulting ChatGPT: ethical dilemmas in language model artificial intelligence[J]. J Am Acad Dermatol, 2023: S0190-9622(23)00364-X. DOI: 10.1016/j.jaad.2023.02.052.
[36]	赵菲菲, 卢蕾, 王靖雯, 等. 基层医疗卫生机构药学人才队伍现状与分析[J]. 贵州医药, 2023, 47(11): 1776-1778. doi: 10.3969/j.issn.1000-744X.2023.11.058

Relative Articles

Supplements(0)

Cited By

Proportional views

Proportional views

通讯作者: 陈斌, bchen63@163.com

1.
沈阳化工大学材料科学与工程学院沈阳 110142

Get Citation

PDF

XML

Article Metrics

Article views (661) PDF downloads(40)

Advances in the application of AI in chronic disease management in primary care

doi: 10.16766/j.cnki.issn.1674-4152.003431

Abstract

References

Proportional views

Catalog

通讯作者: 陈斌, bchen63@163.com

Article Metrics

Proportional views

Related

Advances in the application of AI in chronic disease management in primary care

doi: 10.16766/j.cnki.issn.1674-4152.003431

Abstract

References

Proportional views

Catalog

通讯作者: 陈斌, bchen63@163.com

Article Metrics

Proportional views

Related

Export File

Citation

Format

Content