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Rami J. Oweis
Researcher at Jordan University of Science and Technology
Publications - 30
Citations - 683
Rami J. Oweis is an academic researcher from Jordan University of Science and Technology. The author has contributed to research in topics: Artificial neural network & Carbon nanotube. The author has an hindex of 10, co-authored 29 publications receiving 567 citations.
Papers
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Journal ArticleDOI
Seizure classification in EEG signals utilizing Hilbert-Huang transform
Rami J. Oweis,Enas Abdulhay +1 more
TL;DR: An original tool for EEG signal processing giving physicians the possibility to diagnose brain functionality abnormalities is presented in this paper and results indicate the usefulness of the tool and its use as an efficient diagnostic tool.
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Medical waste management in Jordan: a study at the King Hussein Medical Center.
TL;DR: It was found that the center's administration was reasonably aware of the importance of medical waste management and practiced some of the measures to adequately handle waste generated at the center, but it was also found that significant voids were present that need to be addressed in the future.
QRS Detection and Heart Rate Variability Analysis: A Survey
Rami J. Oweis,Basim O. Al-Tabbaa +1 more
TL;DR: This work reviews in detail the most recent and efficient techniques related to QRS feature extraction and HRV determination all classified and presented in a convenient fashion to facilitate coverage.
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An alternative respiratory sounds classification system utilizing artificial neural networks.
TL;DR: It may be added that utilizing the autocorrelation function in the feature extraction in such applications results in enhanced performance and avoids undesired computation complexities compared to other techniques.
Journal ArticleDOI
An Intelligent Healthcare Management System: A New Approach in Work-order Prioritization for Medical Equipment Maintenance Requests
TL;DR: A novel software system (EQUIMEDCOMP) that is designed to achieve valuable improvements in the maintenance management of medical technology and is expected to improve the reliability of medical equipment and significantly improve safety and cost-efficiency.