Written by Abdeldjalil Khelassi, Sarra-Nassira Yelles-chaouche, Faiza Benais
Parent Category: Year 2017, Volume 9
Category: Volume 9, Issue 5, May 2017
Background: The computer-aided detection of cardiac arrhythmias stills a crucial application in medical technologies. The rule based systems RBS ensure a high level of transparency and interpretability of the obtained results.
Aim: To facilitate the diagnosis of the cardiologists and to reduce the uncertainty made in this diagnosis.
Methods: In this research article, we have realized a classification and automatic recognition of cardiac arrhythmias, by using XML rules that represent the cardiologist knowledge. Thirteen experiments with different knowledge bases were realized for improving the performance of the used method in the detection of 13 cardiac arrhythmias. In the first 12 experiments, we have designed a specialized knowledge base for each cardiac arrhythmia, which contains just one arrhythmia detection rule. In the last experiment, we applied the knowledge base which contains rules of 12 arrhythmias. We used, for the experiments, an international data set with 279 features and 452 records characterizing 12 leads of ECG signal and social information of patients. The data sets were constructed and published at Bilkent University of Ankara, Turkey. In addition, the second version of the self-developed software “XMLRULE” was used; the software can infer more than one class and facilitate the interpretability of the obtained results.
Results: The 12 first experiments give 82.80% of correct detection as the mean of all experiments, the results were between 19% and 100% with a low rate in just one experiment. The last experiment in which all arrhythmias are considered, the results of correct detection was 38.33% with 90.55% of sensibility and 46.24% of specificity. It was clearly show that in these results the good choice of the classification model is very beneficial in terms of performance. The obtained results were better than the published results with other computational methods for the mono class detection, but it was less in multi-class detection.
Conclusion: The RBS is the most transparent method for cardiac arrhythmias detection and multi arrhythmias detection. It improves an exceptional recognition of arrhythmias, but due to conflicts between rules, multi-arrhythmias and uncertainty of measures, the rate of correct classification was less than the other methods.
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Keywords: Rule based system RBS, Extensible Markup Language XML, Cardiac Arrhythmias, Electrocardiogram ECG
Volume 12, Issue 3, July-September 2020
The worldwide spread of COVID-19 as an emerging, rapidly evolving situation, and the dramatic need of urgent medicine or vaccine, has rapidly brought new hypotheses for pathophysiology and potential medicinal agents to the fore. It is crucial that the research community provide a way to publish this research in a timely manner.
To contribute to this important public health discussion, the Electronic Physician Journal is excited to announce a fast-track procedure to help researchers publish their articles on COVID-19 related subjects that fall under the broad definition of public health, internal medicine, and pharmacology. We are especially welcome to all hypotheses about the pathological basis of the COVID-19 infection and the possible characteristics of potential medicine and vaccine. Submit your manuscript here
The 6th World Conference on Research Integrity (WCRI) is to be held on June 2-5, 2019 in Hong Kong.
The WCRI is the largest and most significant international conference on research integrity. Since the first conference in Lisbon in 2007, it has given researchers, teachers, funding agencies, government officials, journal editors, senior administrators, and research students opportunities to share experiences and to discuss and promote integrity in research. Read more:
TDR Clinical Research and Development Fellowships
Call for applications
Deadline for submission: 7 March 2019, 16:00 (GMT)
TDR provides fellowships for early- to mid-career researchers and clinical trial staff (e.g. clinicians, pharmacists, medical statisticians, data managers, other health researchers) in low- and middle-income countries (LMICs) to learn how to conduct clinical trials. Read more:
Meta-Analysis Workshops in New York, USA, and London, UK, in April and May 2019
Don't miss this exceptional opportunity to learn how to perform and report a Meta-analysis correctly. Two Meta-analysis workshops are organized in April and May 2019 by Dr. Michael Borenstein in New York, USA (April 08-10, 2019) and London, UK (May 27-29).
About the Instructor
Dr. Michael Borenstein, one of the authors of Introduction to Meta-Analysis, is widely recognized for his ability to make statistical concepts accessible to researchers as well as to statisticians. He has lectured widely on meta-analysis, including at the NIH, CDC, and FDA. Read more: