[1] |
张兴文, 祝益民, 刘智玲, 等. 老年慢性病人群健康服务的困境与应对[J]. 中国全科医学, 2016, 19(36): 4434-4437. doi: 10.3969/j.issn.1007-9572.2016.36.006
|
[2] |
World Health Organization. World report on ageing and health. Geneva: World Health Organization (WHO)[M]. https://www.who.int/publications/i/item/9789241565042.2015-9-29/2019-10-15.
|
[3] |
The Lancet. GBD 2017: A fragile world[J]. Lancet, 2018, 392(10159): 1683. doi: 10.1016/S0140-6736(18)32858-7
|
[4] |
史弘毅. 中国人口老龄化带来的健康问题及其相关策略[J]. 临床医药文献电子杂志, 2018, 5(84): 174-175. doi: 10.3877/j.issn.2095-8242.2018.84.147
|
[5] |
武留信, 朱玲, 陈志恒, 等. 中国健康管理与健康产业发展报告(2018)[M]. 北京: 社会科学文献出版社, 2019.
|
[6] |
屈健宁, 王浩, 梅浙川, 等. 互联网+慢性病管理创新模式探索[J]. 重庆医学, 2017, 46(7): 988-989. doi: 10.3969/j.issn.1671-8348.2017.07.040
|
[7] |
吕兰婷, 林筑, 张延. 我国慢性病防控与管理研究的十年综述[J]. 中国卫生事业管理, 2020, 37(1): 32-34, 37. https://www.cnki.com.cn/Article/CJFDTOTAL-ZWSG202001012.htm
|
[8] |
李文玲. 慢性病管理模式现状分析[J]. 医学理论与实践, 2018, 31(22): 3353-3354. https://www.cnki.com.cn/Article/CJFDTOTAL-YXLL201822014.htm
|
[9] |
张延, 田雯, 徐梦霞, 等. 基于ICCC模型的北京市朝阳区慢性病管理模型剖析和启示[J]. 中国初级卫生保健, 2018, 32(6): 27-31. doi: 10.3969/j.issn.1001-568X.2018.06.0011
|
[10] |
唐星月, 张清. 国内外慢性病管理模式的比较研究[J]. 中国全科医学, 2017, 20(9): 1025-1030. doi: 10.3969/j.issn.1007-9572.2017.09.002
|
[11] |
Government account ability office. Health information technology: HHS should assess the effectiveness of its efforts to enhance patient access to, use of electronic health information[N]. US Fed News Service, Including US State News[Washington, D.C. ]. 2017-03-15.
|
[12] |
孟群, 尹新, 陈禹. 互联网+慢病管理的研究与实践[J]. 中国卫生信息管理杂志, 2016, 13(2): 119-123. https://www.cnki.com.cn/Article/CJFDTOTAL-WSGL201602007.htm
|
[13] |
邵红霞, 武俊平, 吴琦. 重视慢病防控与传染病的防治关联[J]. 中国慢性病预防与控制, 2020, 28(8): 561-562. https://www.cnki.com.cn/Article/CJFDTOTAL-ZMXB202008001.htm
|
[14] |
MARTINI N, PICCINNI C, PEDRINI A, et al. COVID-19 and chronic diseases: Current knowledge, future steps and the MaCroScopio project[J]. Recenti Prog Med, 2020, 111(4): 198-201.
|
[15] |
TAL-SINGER R, CRAPO J D. COPD at the time of COVID-19: A COPD foundation perspective[J]. Chronic Obstr Pulm Dis, 2020, 7(2): 73-75.
|
[16] |
KWONG E W, WU H, PANG G K, et al. A prediction model of blood pressure for telemedicine[J]. Health Informatics J, 2018, 24(3): 227-244. doi: 10.1177/1460458216663025
|
[17] |
张宝露, 孙子科技木, 鞠梅, 等. 基于物联网云计算技术的远程医疗在老年慢性病管理中的研究进展[J]. 中国老年学杂志, 2017, 37(11): 2835-2838. doi: 10.3969/j.issn.1005-9202.2017.11.105
|
[18] |
应志野, 李春漾, 曾筱茜, 等. 物联网在慢性肾脏病管理中的应用[J]. 华西医学, 2019, 34(7): 827-831. https://www.cnki.com.cn/Article/CJFDTOTAL-HXYX201907019.htm
|
[19] |
YANG C, KONG G, WANG L, et al. Big data in nephrology: Are we ready for the change?[J]. Nephrology, 2019, 24(11): 1097-1102. doi: 10.1111/nep.13636
|
[20] |
BHARDWAJ N, WODAJO B, SPANO A, et al. The impact of big data on chronic disease management[J]. Health Care Manag, 2018, 37(1): 90-98. doi: 10.1097/HCM.0000000000000194
|
[21] |
WILLEMS S M, ABELN S, FEENSTRA K A, et al. The potential use of big data in oncology[J]. Oral Oncol, 2019, 98: 8-12. doi: 10.1016/j.oraloncology.2019.09.003
|
[22] |
王琛琛, 洪忻, 秦真真, 等. 南京市社区高血压患者自我管理项目效果评估[J]. 中华疾病控制杂志, 2016, 20(10): 975-978. https://www.cnki.com.cn/Article/CJFDTOTAL-JBKZ201610002.htm
|
[23] |
王睆琳, 李景宇, 谭明英. 我国互联网+慢性病管理模式应用前景分析[J]. 中国卫生信息管理杂志, 2020, 17(2): 168-171, 187. https://www.cnki.com.cn/Article/CJFDTOTAL-WSGL202002010.htm
|
[24] |
国务院办公厅. 国务院办公厅关于制定和实施老年人照顾服务项目的意见(国办发〔2017〕52号)[EB/OL]. (2017-06-16)[2020-06-15]. http://www.gov.cn/zhengce/content/2017-06/16/content_5203088.htm.
|
[25] |
国务院. 国务院印发《"十三五"深化医药卫生体制改革规划》[J]. 中国医院院长, 2017(Z1): 10. https://www.cnki.com.cn/Article/CJFDTOTAL-YYYZ2017Z1002.htm
|
[26] |
孙娟, 乔平安. 基于物联网的老年人健康管理系统的设计与应用[J]. 中国新通信, 2018, 20(2): 124-125. doi: 10.3969/j.issn.1673-4866.2018.02.103
|
[27] |
ORNES S. Core Concept: The Internet of Things and the explosion of interconnectivity[J]. Proc Nati Acad of Sci U S A, 2016, 113(40): 11059-11060. doi: 10.1073/pnas.1613921113
|
[28] |
王红. 基于大数据社区养老模式研究与探索[J]. 电脑知识与技术: 学术交流, 2018, 14(9): 249-250. https://www.cnki.com.cn/Article/CJFDTOTAL-DNZS201825108.htm
|
[29] |
李涵, 李慧嘉, 张林姿, 等. 大数据环境下老年人失能失智因素关联[J]. 计算机科学, 2018, 45(S1): 497-501. https://www.cnki.com.cn/Article/CJFDTOTAL-JSJA2018S1107.htm
|
[30] |
National Comprehensive Cancer Network. Clinical Practice Guidelines in Oncology: Lung Cancer Screening(Version 1.2020). https://www.nccn.org/professionals/physician_gls/default.aspx.
|
[31] |
UEMATSU T, NAKASHIMA K, KIKUCHI M, et al. The Japanese breast cancer society clinical practice guidelines for breast cancer screening and diagnosis, 2018 edition[J]. Breast Cancer, 2020, 27(1): 17-24. doi: 10.1007/s12282-019-01025-7
|
[32] |
PENA A S, CURRAN J A, FUERY M, et al. Screening, assessment and management of type 2 diabetes mellitus in children and adolescents: Australasian Paediatric Endocrine Group guidelines[J]. Med J Aust, 2020, 213(1): 30-43. doi: 10.5694/mja2.50666
|
[33] |
王逸, 殷安康, 赵翔宇. 基于互联网平台的慢性病管理研究[J]. 中国农村卫生, 2019, 11(20): 17. doi: 10.3969/j.issn.1674-361X.2019.20.020
|
[34] |
LEBLANC E L, PATNODE C D, WEBBER E M, et al. Behavioral and pharmacotherapy weight loss interventions to prevent obesity-related morbidity and mortality in adults: An updated systematic review for the U.S. preventive services task force[J]. JAMA, 2018, 320(11): 1172-1191. doi: 10.1001/jama.2018.7777
|
[35] |
LEE W, HWANG S H, CHOI H, et al. The association between smoking or passive smoking and cardiovascular diseases using a Bayesian hierarchical model: Based on the 2008-2013 Korea Community Health Survey[J]. Epidemiol Health, 2017, 22;39: e2017026.
|
[36] |
CHARTRANG G, CHENG P M, VORONSOV E, et al. Deep learning: A primer for radiologists[J]. Radio graphics, 2017, 37(7): 2113-2131.
|
[37] |
赵梦蝶, 孙九爱. 机器学习在心血管疾病诊断中的研究进展[J]. 北京生物医学工程, 2020, 39(2): 208-214. doi: 10.3969/j.issn.1002-3208.2020.02.015
|
[38] |
ESTEVA A, KUPREL B, NOVOA R A, et al. Dermatologist-level classification of skin cancer with deep neural networks[J]. Nature, 2017, 542(7639): 115-118. doi: 10.1038/nature21056
|
[39] |
LIU Y, KOHLERGER T, NOROUZI M, et al. Artificial intelligence-based breast cancer nodal metastasis detection: Insights into the black box for pathologists[J]. Arch Pathol Lab Med, 2019, 143(7): 859-868. doi: 10.5858/arpa.2018-0147-OA
|
[40] |
SINGH G, AL'AREF SJ, VAN ASSEN M, et al. Machine learning in cardiac CT: Basic concepts and contemporary data[J]. J Cardiovasc Comput Tomogr, 2018, 12(3): 192-201. doi: 10.1016/j.jcct.2018.04.010
|
[41] |
CHEN M, HAO Y, HWANG K, et al. Disease prediction by machine learning over big data from healthcare communities[J]. IEEE Access, 2017, 5: 8869-8879. doi: 10.1109/ACCESS.2017.2694446
|
[42] |
彭苏元. 基于机器学习方法的CKD4期中医慢病管理疾病预测模型的建立与验证[D]. 广州: 广州中医药大学, 2019.
|
[43] |
帅仁俊, 陈平, 马力, 等. 基于AI的慢病高危管理系统研究与设计[J]. 中国数字医学, 2019, 14(1): 21-23. doi: 10.3969/j.issn.1673-7571.2019.01.006
|
[44] |
赵笑颜, 王嘉阳, 王昀, 等. 大数据在慢病管理中的应用[J]. 解放军医院管理杂志, 2019, 6(1): 1-4. https://www.cnki.com.cn/Article/CJFDTOTAL-JFYG201901005.htm
|
[45] |
黄焯. 基于云计算与医疗大数据的FP-Growth算法的优化研究[D]. 泉州: 华侨大学, 2018.
|
[46] |
朱甜甜. 基于医疗大数据的肿瘤疾病模式分析与研究[D]. 青岛: 青岛科技大学, 2018.
|
[47] |
王伟娜, 杨丹, 童庆. 基于大数据的慢病管理平台的研究[J]. 电脑知识与技术, 2018, 14(5): 27-29. https://www.cnki.com.cn/Article/CJFDTOTAL-DNZS201805011.htm
|
[48] |
姜媛媛, 王晶晶, 张伟宏, 等. "互联网+"在慢性病管理中的应用研究进展[J]. 现代医药卫生, 2019, 35(5): 692-695. doi: 10.3969/j.issn.1009-5519.2019.05.017
|