IoMT Tsukamoto Type-2 fuzzy expert system for tuberculosis and Alzheimer’s disease

M.K. Sharma , Nitesh Dhiman , Ajendra Sharma , Tarun Kumar
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Abstract

Accurate disease monitoring is an extremely time-consuming task for medical experts and technocrats involved, requiring technical support for diagnostic systems. To overcome this situation, we developed an Internet of Medical Things (IoMT) based on Tsukamoto Type 2 Fuzzy Inference System (TT2FIS) that can easily handle diagnostic and predictive aspects in the medical field. In the proposed system, we developed a Tsukamoto type 2 fuzzy inference system that takes the patient’s symptoms as input factors and the medical device as the output factor of the result. The aim of this work is to demonstrate the usefulness of type 2 fuzzy sets in Tuberculosis and Alzheimer’s disease diagnostic system. Numerical calculations are also performed to illustrate the applicability of the proposed method. A validation of the proposed derivation of the proposed IoMT model is also discussed in the results and conclusions section.

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治疗结核病和阿尔茨海默病的 IoMT Tsukamoto Type-2 模糊专家系统
对于医学专家和相关技术人员来说,精确的疾病监测是一项极其耗时的任务,需要诊断系统的技术支持。为了克服这种情况,我们开发了一种基于塚本 2 型模糊推理系统(TT2FIS)的医疗物联网(IoMT),可以轻松处理医疗领域的诊断和预测问题。在提议的系统中,我们开发了一个塚本 2 型模糊推理系统,该系统将病人的症状作为输入因素,将医疗设备作为结果的输出因素。这项工作的目的是证明 2 型模糊集在结核病和阿尔茨海默病诊断系统中的实用性。同时还进行了数值计算,以说明所提方法的适用性。结果和结论部分还讨论了对拟议 IoMT 模型推导的验证。
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