Loh Brian C S, Then Patrick H H
Swinburne University of Technology Sarawak Campus, Kuching, Sarawak, Malaysia.
Mhealth. 2017 Oct 19;3:45. doi: 10.21037/mhealth.2017.09.01. eCollection 2017.
Cardiovascular diseases are one of the top causes of deaths worldwide. In developing nations and rural areas, difficulties with diagnosis and treatment are made worse due to the deficiency of healthcare facilities. A viable solution to this issue is telemedicine, which involves delivering health care and sharing medical knowledge at a distance. Additionally, mHealth, the utilization of mobile devices for medical care, has also proven to be a feasible choice. The integration of telemedicine, mHealth and computer-aided diagnosis systems with the fields of machine and deep learning has enabled the creation of effective services that are adaptable to a multitude of scenarios. The objective of this review is to provide an overview of heart disease diagnosis and management, especially within the context of rural healthcare, as well as discuss the benefits, issues and solutions of implementing deep learning algorithms to improve the efficacy of relevant medical applications.
心血管疾病是全球主要死因之一。在发展中国家和农村地区，由于医疗设施不足，诊断和治疗困难加剧。解决这一问题的一个可行办法是远程医疗，即远程提供医疗保健和分享医学知识。此外，移动医疗（利用移动设备进行医疗保健）也已被证明是一种可行的选择。远程医疗、移动医疗和计算机辅助诊断系统与机器学习和深度学习领域的整合，催生了适用于多种场景的有效服务。本综述的目的是概述心脏病的诊断和管理，特别是在农村医疗保健背景下，并讨论实施深度学习算法以提高相关医疗应用疗效的益处、问题和解决方案。
