دانلود مقاله انگلیسی رایگان:HealthFog: یک سیستم هوشمند درمانی هوشمند مبتنی بر یادگیری عمیق برای تشخیص خودکار بیماری های قلبی در محیط های IoT و محاسبات مه - 2020
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  • HealthFog: An ensemble deep learning based Smart Healthcare System for Automatic Diagnosis of Heart Diseases in integrated IoT and fog computing environments HealthFog: An ensemble deep learning based Smart Healthcare System for Automatic Diagnosis of Heart Diseases in integrated IoT and fog computing environments
    HealthFog: An ensemble deep learning based Smart Healthcare System for Automatic Diagnosis of Heart Diseases in integrated IoT and fog computing environments

    سال انتشار:

    2020


    عنوان انگلیسی مقاله:

    HealthFog: An ensemble deep learning based Smart Healthcare System for Automatic Diagnosis of Heart Diseases in integrated IoT and fog computing environments


    ترجمه فارسی عنوان مقاله:

    HealthFog: یک سیستم هوشمند درمانی هوشمند مبتنی بر یادگیری عمیق برای تشخیص خودکار بیماری های قلبی در محیط های IoT و محاسبات مه


    منبع:

    Sciencedirect - Elsevier - Future Generation Computer Systems, 104 (2020) 187-200: doi:10:1016/j:future:2019:10:043


    نویسنده:

    Shreshth Tuli a,b,∗, Nipam Basumatary a,c, Sukhpal Singh Gill d, Mohsen Kahani a,e, Rajesh Chand Arya f, Gurpreet Singh Wander f, Rajkumar Buyya a


    چکیده انگلیسی:

    Cloud computing provides resources over the Internet and allows a plethora of applications to be deployed to provide services for different industries. The major bottleneck being faced currently in these cloud frameworks is their limited scalability and hence inability to cater to the requirements of centralized Internet of Things (IoT) based compute environments. The main reason for this is that latency-sensitive applications like health monitoring and surveillance systems now require computation over large amounts of data (Big Data) transferred to centralized database and from database to cloud data centers which leads to drop in performance of such systems. The new paradigms of fog and edge computing provide innovative solutions by bringing resources closer to the user and provide low latency and energy efficient solutions for data processing compared to cloud domains. Still, the current fog models have many limitations and focus from a limited perspective on either accuracy of results or reduced response time but not both. We proposed a novel framework called HealthFog for integrating ensemble deep learning in Edge computing devices and deployed it for a real-life application of automatic Heart Disease analysis. HealthFog delivers healthcare as a fog service using IoT devices and efficiently manages the data of heart patients, which comes as user requests. Fog-enabled cloud framework, FogBus is used to deploy and test the performance of the proposed model in terms of power consumption, network bandwidth, latency, jitter, accuracy and execution time. HealthFog is configurable to various operation modes which provide the best Quality of Service or prediction accuracy, as required, in diverse fog computation scenarios and for different user requirements.
    Keywords: Fog computing | Internet of things | Healthcare | Deep learning | Ensemble learning | Heart patient analysis


    سطح: متوسط
    تعداد صفحات فایل pdf انگلیسی: 14
    حجم فایل: 2528 کیلوبایت

    قیمت: رایگان


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