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صفحه اصلی
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هشتمین کنفرانس بین المللی فناوری و مدیریت انرژی
Disease Diagnosis and Data Protection System for IoT-based Wearable Sensor Network
نویسندگان :
Erfan Haghighat khah
1
Mehdi Golsorkhtabaramiri
2
1- دانشگاه آزاد اسلامی واحد بابل
2- دانشگاه آزاد اسلامی واحد بابل
کلمات کلیدی :
Support Vector Regression،Emprical Mode Decompoition
چکیده :
Big Data analytics is used in many areas of smart healthcare. Leakage or correction of this data while transferring is not only violating patients' privacy but endangering their exists. Many scientists have worked on encoded Personal Health Records (PHR). However, there are still challenges such as data leakage while learning, and training models leakage and some users do not like to breach their data in the analytics organization. How to protect privacy while using learning is an important issue. This paper presents a system for forecasting disease and timely alerts by collecting data from sensors, and using Empirical Mode Decomposition (EMD) and Support Vector Regression (SVR) to analyze and monitor patient health data. In order to protect health data privacy, we adopt a secure data deletion approach, whereby the data owner will be able to choose to deny some users admission to their health data. The presented analysis and the experimental results show the safety and efficacy of our proposed approach.
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بیشتر
ثمین همایش، سامانه مدیریت کنفرانس ها و جشنواره ها - نگارش 43.8.1
