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دسته بندی:
هوش مصنوعی - Artificial intelligence
سال انتشار:
2020
عنوان انگلیسی مقاله:
Analyzing patient health information based on IoT sensor with AI for improving patient assistance in the future direction
ترجمه فارسی عنوان مقاله:
تجزیه و تحلیل اطلاعات سلامت بیمار مبتنی بر حسگر اینترنت اشیا با هوش مصنوعی برای بهبود کمک به بیمار در مسیر آینده
منبع:
Sciencedirect - Elsevier - Measurement, 159 (2020) 107757. doi:10.1016/j.measurement.2020.107757
نویسنده:
H. Fouad a,b,⇑, Azza S. Hassanein b, Ahmed M. Soliman b, Haytham Al-Feel c
چکیده انگلیسی:
Internet of Things (IoT) and Artificial Intelligence (AI) play a vital role in the upcoming years to improve
the assistance systems. The IoT devices utilize several sensor devices that able to collect a large volume of
data in different domains which is processed by AI techniques to make the decision about the assistance
problems. Among several applications, in this work, IoT with AI is used to examine the healthcare sectors
to improve patient assistance and patient care in the future direction. Traditional health care assistance
system fails to predict the exact patient health information and needs which reduces the accuracy of
patient assistance process. For these issues, an IoT sensor with AI is used to predict the exact patient
details such as fitness tracker, medical reports, health activity, body mass, temperature, and other health
care information which helps to choose the right assistance process. Healthcare mobile application is
used to achieve this goal and collect the patient’s information. This information is shared in the cloud
environment, which is accessed and processed by applying the optimized machine learning techniques.
The gathered patient details are processed according to the iterative golden section optimized deep belief
neural network (IGDBN). The introduced network examines the patient’s details from the previous health
information which helps to predict the exact patient health condition in the future direction. The efficiency
of IoT sensor with an AI-based health assistance prediction process is developed using MATLAB
tool. Excellence is determined in terms of precision (99.87), loss error (0.045), simple matching coefficient
(99.71%), Matthews correlation coefficient (99.10%) and accuracy (99.86%).
Keywords: IoT | Sensor | AI | Patient health condition | Mobile application | MATLAB
قیمت: رایگان
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