相似文献
1
Digital health approaches for cardiovascular diseases prevention and management: lessons from preliminary studies.
Mhealth. 2021 Jul 20;7:41. doi: 10.21037/mHealth-2020-6. eCollection 2021.
2
Lessons Learned From Using Focus Groups to Refine Digital Interventions.
JMIR Res Protoc. 2015 Jul 31;4(3):e95. doi: 10.2196/resprot.4404.
3
Implementing Artificial Intelligence and Digital Health in Resource-Limited Settings? Top 10 Lessons We Learned in Congenital Heart Defects and Cardiology.
OMICS. 2020 May;24(5):264-277. doi: 10.1089/omi.2019.0142. Epub 2019 Oct 8.
4
A Digital Health Intervention for Weight Management for Latino Families Living in Rural Communities: Perspectives and Lessons Learned During Development.
JMIR Form Res. 2020 Aug 20;4(8):e20679. doi: 10.2196/20679.
5
Reducing the Global Burden of Cardiovascular Disease, Part 2: Prevention and Treatment of Cardiovascular Disease.
Circ Res. 2017 Sep 1;121(6):695-710. doi: 10.1161/CIRCRESAHA.117.311849.
6
How Digital Health Can Be Applied for Preventing and Managing Hypertension.
Curr Hypertens Rep. 2019 Apr 22;21(5):40. doi: 10.1007/s11906-019-0940-0.
7
Global Perspectives on Improving Chronic Disease Prevention and Management in Diverse Settings.
Prev Chronic Dis. 2021 Apr 8;18:E33. doi: 10.5888/pcd18.210055.
8
[VIVOPTIM: Feedback of an e-Health experimental program of primary prevention of cardiovascular risk on 30 to 70 years old volunteers].
Ann Cardiol Angeiol (Paris). 2018 Nov;67(5):293-299. doi: 10.1016/j.ancard.2018.09.002. Epub 2018 Oct 6.
9
Assessing the digital economy: aims, frameworks, pilots, results, and lessons.
J Innov Entrep. 2020;9(1):16. doi: 10.1186/s13731-020-00129-1. Epub 2020 Sep 7.
10
Training in Cardiovascular Epidemiology and Prevention: A 50-Year Journey From Makarska to Goa.
Glob Heart. 2018 Dec;13(4):355-362. doi: 10.1016/j.gheart.2018.09.526.
引用本文的文献
1
Digital Health Solutions for Cardiovascular Disease Prevention: Systematic Review.
J Med Internet Res. 2025 Jan 23;27:e64981. doi: 10.2196/64981.
2
Evaluating a New Digital App-Based Program for Heart Health: Feasibility and Acceptability Pilot Study.
JMIR Form Res. 2024 May 24;8:e50446. doi: 10.2196/50446.
3
Stakeholder-led understanding of the implementation of digital technologies within heart disease diagnosis: a qualitative study protocol.
BMJ Open. 2023 Jun 27;13(6):e072952. doi: 10.1136/bmjopen-2023-072952.
4
The Potential Role of Digital Health in Obesity Care.
Adv Ther. 2022 Oct;39(10):4397-4412. doi: 10.1007/s12325-022-02265-4. Epub 2022 Aug 4.
5
Medical students' intention to integrate digital health into their medical practice: A pre-peri COVID-19 survey study in Canada.
Digit Health. 2022 Jul 21;8:20552076221114195. doi: 10.1177/20552076221114195. eCollection 2022 Jan-Dec.
6
Machine learning models for prediction of co-occurrence of diabetes and cardiovascular diseases: a retrospective cohort study.
J Diabetes Metab Disord. 2022 Jan 12;21(1):251-261. doi: 10.1007/s40200-021-00968-z. eCollection 2022 Jun.
7
Use of Digital Health Interventions in Sub-Saharan Africa for Health Systems Strengthening Over the Last 10 Years: A Scoping Review Protocol.
Front Digit Health. 2022 May 6;4:874251. doi: 10.3389/fdgth.2022.874251. eCollection 2022.
8
Machine Learning Approaches for Predicting Hypertension and Its Associated Factors Using Population-Level Data From Three South Asian Countries.
Front Cardiovasc Med. 2022 Mar 31;9:839379. doi: 10.3389/fcvm.2022.839379. eCollection 2022.
9
Prediction of cardiac autonomic neuropathy using a machine learning model in patients with diabetes.
Ther Adv Endocrinol Metab. 2022 Mar 22;13:20420188221086693. doi: 10.1177/20420188221086693. eCollection 2022.
10
Factors Associated with Chronic Kidney Disease in Patients with Type 2 Diabetes in Bangladesh.
Int J Environ Res Public Health. 2021 Nov 23;18(23):12277. doi: 10.3390/ijerph182312277.
本文引用的文献
1
Artificial intelligence: opportunities and risks for public health.
Lancet Digit Health. 2019 May;1(1):e13-e14. doi: 10.1016/S2589-7500(19)30002-0. Epub 2019 May 2.
2
WhatsApp in : an overview on the potentialities and the opportunities in medical imaging.
Mhealth. 2020 Apr 5;6:19. doi: 10.21037/mhealth.2019.11.01. eCollection 2020.
3
Prevention and management of CVD in LMICs: why do ethnicity, culture, and context matter?
BMC Med. 2020 Jan 24;18(1):7. doi: 10.1186/s12916-019-1480-9.
4
Artificial Intelligence and Machine Learning in Cardiovascular Health Care.
Ann Thorac Surg. 2020 May;109(5):1323-1329. doi: 10.1016/j.athoracsur.2019.09.042. Epub 2019 Nov 7.
5
Mobile phone text-messaging interventions aimed to prevent cardiovascular diseases (Text2PreventCVD): systematic review and individual patient data meta-analysis.
Open Heart. 2019 Oct 9;6(2):e001017. doi: 10.1136/openhrt-2019-001017. eCollection 2019.
6
Validation and Acceptability of a Cuffless Wrist-Worn Wearable Blood Pressure Monitoring Device Among Users and Health Care Professionals: Mixed Methods Study.
JMIR Mhealth Uhealth. 2019 Sep 14;7(10):e14706. doi: 10.2196/14706.
7
The Cost-Effectiveness of Digital Health Interventions on the Management of Cardiovascular Diseases: Systematic Review.
J Med Internet Res. 2019 Jun 17;21(6):e13166. doi: 10.2196/13166.
8
ESC e-Cardiology Working Group Position Paper: Overcoming challenges in digital health implementation in cardiovascular medicine.
Eur J Prev Cardiol. 2019 Jul;26(11):1166-1177. doi: 10.1177/2047487319832394. Epub 2019 Mar 27.
9
mHealth Interventions for Exercise and Risk Factor Modification in Cardiovascular Disease.
Exerc Sport Sci Rev. 2019 Apr;47(2):86-90. doi: 10.1249/JES.0000000000000185.
10
Effect of text messaging on depression in patients with coronary heart disease: a substudy analysis from the TEXT ME randomised controlled trial.
BMJ Open. 2019 Feb 20;9(2):e022637. doi: 10.1136/bmjopen-2018-022637.
Zotero 插件