IEEE Rev Biomed Eng. 2024;17:197-211. doi: 10.1109/RBME.2022.3186828. Epub 2024 Jan 12.
Target 3.4 of the third Sustainable Development Goal (SDG) of the United Nations (UN) General Assembly proposes to reduce premature mortality from non-communicable diseases (NCDs) by one-third. Epidemiological data presented by the World Health Organization (WHO) in 2016 show that out of a total of 57 million deaths worldwide, approximately 41 million deaths occurred due to NCDs, with 78% of such deaths occurring in low-and-middle-income countries (LMICs). The majority of investigations on NCDs agree that the leading risk factor for mortality worldwide is hypertension. Over 75% of the world's mobile phone subscriptions reside in LMICs, hence making the mobile phone particularly relevant to mHealth deployment in Africa. This study is aimed at determining the scope of the literature available on hypertension diagnosis and management in Africa, with particular emphasis on determining the feasibility, acceptability and effectiveness of interventions based on the use of mobile phones. The bulk of the evidence considered overwhelmingly shows that SMS technology is yet the most used medium for executing interventions in Africa. Consequently, the need to define novel and superior ways of providing effective and low-cost monitoring, diagnosis, and management of hypertension-related NCDs delivered through artificial intelligence and machine learning techniques is clear.
联合国大会可持续发展目标 3.4 提出，将非传染性疾病导致的过早死亡率降低三分之一。世界卫生组织（WHO）2016 年公布的流行病学数据显示，在全球总计 5700 万例死亡中，约有 4100 万人死于非传染性疾病，其中 78%的死亡发生在中低收入国家（LMICs）。大多数关于非传染性疾病的研究都认为，全球死亡率的主要危险因素是高血压。全球超过 75%的手机用户都在 LMICs，这使得手机特别适用于在非洲开展移动医疗。本研究旨在确定非洲有关高血压诊断和管理的文献范围，特别关注基于手机使用的干预措施的可行性、可接受性和有效性。大量证据表明，短信技术仍然是在非洲执行干预措施最常用的手段。因此，显然需要定义新的和更好的方法，通过人工智能和机器学习技术提供有效的、低成本的与高血压相关的非传染性疾病监测、诊断和管理。
