Şimşek Hakan, Yangın Elifnaz
Antalya Bilim Üniversitesi, Antalya, Turkey.
Health Technol (Berl). 2022;12(2):569-582. doi: 10.1007/s12553-021-00624-9. Epub 2022 Jan 27.
COVID-19 disease is an outbreak that seriously affected the whole world, occurred in December 2019, and thus was declared a global epidemic by WHO (World Health Organization). To reduce the impact of the epidemic on humans, it is important to detect the symptoms of the disease in a timely and accurate manner. Recently, several new variants of COVID-19 have been identified in the United Kingdom (UK), South Africa, Brazil and India, and preliminary findings have been suggested that these mutations increase the transmissibility of the virus. Therefore, the aim of this study is to construct a support system based on fuzzy logic for experts to help detect of COVID-19 infection risk in a timely and accurate manner and to get a numerical output on symptoms of the virus from every person. The decision support system consists of three different sub and one main Mamdani type fuzzy inference systems (FIS). Subsystems are Common- Serious symptoms (First), Rare Symptoms (Second) and Personal Information (Third). The first FIS has five inputs, fever-time, cough-time, fatigue-time, shortness of breath and chest pain/dysfunction; the second FIS has four inputs, Loss of Taste/Smell, Body Aches, Conjuctivitis, and Nausea/Vomiting/Diarrhea; and the third FIS has three inputs, Age, Smoke, and Comorbidities. Then, we obtain personal risk index of individual by combining the outputs of these subsystems in a final FIS. The results can be used by health professionals and epidemiologists to make inferences about public health. Numerical output can also be useful for self-control of an individual.
新冠病毒疾病是一场在2019年12月爆发并严重影响全球的疫情，因此被世界卫生组织（WHO）宣布为全球大流行。为了降低疫情对人类的影响，及时准确地检测出该疾病的症状至关重要。最近，在英国、南非、巴西和印度发现了几种新冠病毒的新变种，初步研究结果表明这些突变增加了病毒的传播性。因此，本研究的目的是构建一个基于模糊逻辑的支持系统，以帮助专家及时准确地检测新冠病毒感染风险，并从每个人那里获得关于该病毒症状的数值输出。该决策支持系统由三个不同的子系统和一个主要的Mamdani型模糊推理系统（FIS）组成。子系统分别是常见严重症状（第一个）、罕见症状（第二个）和个人信息（第三个）。第一个模糊推理系统有五个输入，即发热时长、咳嗽时长、疲劳时长、呼吸急促和胸痛/功能障碍；第二个模糊推理系统有四个输入，即味觉/嗅觉丧失、身体疼痛、结膜炎以及恶心/呕吐/腹泻；第三个模糊推理系统有三个输入，即年龄、吸烟情况和合并症。然后，我们通过在最终的模糊推理系统中合并这些子系统的输出，得到个人的风险指数。这些结果可供卫生专业人员和流行病学家用于对公共卫生进行推断。数值输出对个人的自我控制也很有用。
