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Medical students' intention to integrate digital health into their medical practice: A pre-peri COVID-19 survey study in Canada.
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Machine learning models for prediction of co-occurrence of diabetes and cardiovascular diseases: a retrospective cohort study.
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Factors Associated with Chronic Kidney Disease in Patients with Type 2 Diabetes in Bangladesh.
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本文引用的文献

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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.
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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.
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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.
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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.
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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.
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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.

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