A novel healthcare decision support system using IoT and ANFIS

Naveen Kumar Dewangan, Neeti Pandey, Ritu Gautam, Avinash Krishna Goswami, Santosh Rameshwar Mitkari, Amanveer Singh, Anand Kopare, N. Gobi
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Abstract

Modern healthcare facilities are equipped with major difficulties, particularly in poor nations where there are insufficient high-quality hospitals and medical professionals in remote places. Healthcare has profited from artificial intelligence’s revolution in many other areas of life. A few issues with the current architecture of the store-and-forward method of conventional telemedicine are that it requires a local health center with a dedicated staff, medical equipment to prepare patient reports, and long turnaround time for receiving a diagnosis and medication details from a medical expert in a main hospital, the cost of local health centers, and the requirement for a Wi-Fi connection. In this work, we present a new intelligent healthcare system built on cutting-edge technology such as deep learning and the Internet of Things (IoT). This system has the intelligence to use a medical decision support system to sense and process patient data by making use of adaptive neuro fuzzy inference system (ANFIS). For those who live in rural places, this system offers an affordable solution. By contacting local hospitals, users can determine whether they have a serious health concern and seek appropriate treatment. Additionally, the experiment findings demonstrate that the suggested system is capable of providing health services due to its efficiency and intelligence.

Abstract Image

使用物联网和 ANFIS 的新型医疗决策支持系统
现代医疗设施的配备存在很大困难,特别是在贫穷国家,偏远地区没有足够的高质量医院和医疗专业人员。在生活的许多其他领域,医疗保健已经从人工智能革命中获益。目前,传统远程医疗的存储转发方法架构存在一些问题,如需要当地医疗中心配备专门的工作人员、医疗设备来准备病人报告、从大医院的医疗专家那里获得诊断和用药详情的周转时间较长、当地医疗中心的成本以及对 Wi-Fi 连接的要求等。在这项工作中,我们提出了一种基于深度学习和物联网(IoT)等前沿技术的新型智能医疗系统。该系统通过使用自适应神经模糊推理系统(ANFIS),智能地使用医疗决策支持系统来感知和处理患者数据。对于那些生活在农村地区的人来说,该系统提供了一个经济实惠的解决方案。通过与当地医院联系,用户可以确定自己是否有严重的健康问题,并寻求适当的治疗。此外,实验结果表明,所建议的系统因其高效性和智能性,能够提供医疗服务。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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