International Conference on Computer and Knowledge Engineering

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Intelligent Rule Extraction in Complex Event Processing Platform for Health Monitoring Systems

Authors :

Mohammad Mehdi Naseri¹ Shima Tabibian² Elaheh Homayounvala³

1- Cyberspace Research Institute, Shahid Beheshti University 2- Cyberspace Research Institute, Shahid Beheshti University 3- Department of Computing, Goldsmith University of London

Keywords :

Remote health monitoring, User behavior modeling, Complex event processing, Rule-based learning

Abstract :

Taking care of people with disabilities is essential in any situation and its cost is increasing every day. Many intelligent remote health monitoring systems have been developed from the past till now. These systems face challenges such as managing large volumes of data, real-time processing, and rule setting human errors. In this research, a complex event processing (CEP)-based platform is proposed for remote health monitoring and user behavior modeling in a health system. This platform can manage huge amounts of data in real-time. In addition, it can solve human errors in rules setting by extracting rules from the previous data using a rule-based learning method. Moreover, rule-based learning is an explainable method to get feedback from the domain experts. Experimental results in the hospital dataset showed that the PART rule-based learning has better accuracy (about 98.61%) in classifying the health conditions of the patients in comparison to other rule-based methods. On the other hand, the JRip rule-based learning has produced 16 fewer rules with similar accuracy (about 97.32%) compared to the PART classification method. Therefore, the JRip classifier is a better option for generating a small set of rules for using in the CEP engine.

Papers List

List of archived papers

Atlas-based segmentation of cardiac chambers in systolic and diastolic phases of echocardiographic images

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PeQa: a Massive Persian Quenstion-Answering and Chatbot Dataset

Fatemeh Zahra Arshia - Mohammad Ali Keyvanrad - Saeedeh Sadat Sadidpour - Sayyid Mohammad Reza Mohammadi

An Advanced Dual Attention-based U-Net Using Breast Ultrasound Data for Image Segmentation

Erfan Akbarnezhad Sany - Niloufar Asghari - Fatemeh Naserizadeh - Seyyed Abed Hosseini

Enhanced Melanoma Detection: An Improved Deformable DETR Model with Efficient Channel Attention

Amirreza Rouhbakhshmeghrazi - Shayan Nalbandian - Sheida Shadman - Mohammad Reza Hassannezhad - Shuyuan Yang - Bo Li

Energy-Aware Dynamic Digital Twin Placement in Mobile Edge Computing

Mahdi Hematyar - Zeinab Movahedi

Non-Functional Requirement Extracting Methods for AI-based Systems: A Survey

Reza Damirchi - Amineh Amini

Delta-Audit: Explaining What Changes When Models Change

Arshia Hemmat - Afsane Fatemi

Using Deep Learning for Classification of Lung Cancer on CT Images in Ardabil Province

Mohammad Ali Javadzadeh Barzaki - Jafar Abdollahi - Mohammad Negaresh - Maryam Salimi - Hadi Zolfeghari - Mohsen Mohammadi - Asma Salmani - Rona Jannati - Firouz Amani

Computational Microscopy Based on Fourier Ptychography using Embedded Architecture

Rezvan Mir - Abedin Vahedian

Decentralized Federated Learning in IoT Environments: A Hierarchical Approach

Majid Mohammadpour - Seyedakbar Mostafavi