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All Journal International Journal of Evaluation and Research in Education (IJERE) TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Computer Science
Hamza Abu Owida
Al-Ahliyya Amman University
Computer Science & IT Education Electrical & Electronics Engineering

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Non-invasive sensing techniques for glucose detection: a review Jamal Al-Nabulsi; Hamza Abu Owida; Jumana Ma’touq; Sabrina Matar; Esraa Al-Aazeh; Abdelqader Al-Maaiouf; Abdullah Bleibel
Bulletin of Electrical Engineering and Informatics Vol 11, No 4: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i4.3584

Abstract

Diabetes is becoming more prevalent over the world, with approximately 7.8 million new cases diagnosed each year. The most crucial aspect of diabetes therapy is frequent glucose monitoring; the one and only way diabetics can maintain healthy blood sugar standard is through diet and exercise. Blood glucose monitoring techniques have gone through massive transformations over the past few years. Non-invasive procedures outperform invasive and minimally invasive ones in terms of inconvenience, pain, and recovery time. Thus, this review aims to explore the latest tools for non-invasive glucose monitoring sensors and techniques. The study showed that non-invasive techniques such as optical and non-optical techniques are better than invasive techniques in terms of accuracy, reliability, repeatability, and ease of use. The study also uncovered that the photoacoustic spectroscopy and ultrasonic techniques have room for further development and advancement considering their flexible nature. The work also proved that the ultrasonic technique is the most promising approach, in conclusion.
Carbon nanomaterials advancements for biomedical applications Hamza Abu Owida; Nidal M. Turab; Jamal Al-Nabulsi
Bulletin of Electrical Engineering and Informatics Vol 12, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i2.4310

Abstract

The development of new technologies has helped tremendously in delivering timely, appropriate, acceptable, and reasonably priced medical treatment. Because of developments in nanoscience, a new class of nanostructures has emerged. Nanomaterials, because of their small size, display exceptional physio-chemical capabilities such as enhanced absorption and reactivity, increased surface area, molar extinction coefficients, tunable characteristics, quantum effects, and magnetic and optical properties. Researchers are interested in carbon-based nanomaterials due to their unique chemical and physical properties, which vary in thermodynamic, biomechanical, electrical, optical, and structural aspects. Due to their inherent properties, carbon nanomaterials, including fullerenes, graphene, carbon nanotubes (CNTs), and carbon nanofibers (CNFs), have been intensively studied for biomedical applications. This article is a review of the most recent findings about the development of carbon-based nanomaterials for use in biosensing, drug delivery, and cancer therapy, among other things.
Deep learning algorithms to improve COVID-19 classification based on CT images Hamza Abu Owida; Hassan S. Migdadi; Omar Salah Mohamed Hemied; Nawaf Farhan Fankur Alshdaifat; Suhaila Farhan Ahmad Abuowaida; Rami S. Alkhawaldeh
Bulletin of Electrical Engineering and Informatics Vol 11, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i5.3802

Abstract

In response to the growing threat posed by COVID-19, several initiatives have been launched to develop methods of halting the progression of the disease. In order to diagnose the COVID-19 infection, testing kits were utilized; however, the use of these kits is time-consuming and suffers from a lack of quality control measures. Computed tomography is an essential part of the diagnostic process in the treatment of COVID-19 (CT). The process of disease detection and diagnosis could be sped up with the help of automation, which would cut down on the number of exams that need to be carried out. A number of recently developed deep learning tools make it possible to automate the Covid-19 scanning process in CT scans and provide additional assistance. This paper investigates how to quickly identify COVID-19 using computational tomography (CT) scans, and it does so by using a deep learning technique that is derived from improving ResNet architecture. In order to test the proposed model, COVID-19 CT scans that include a patient-based split are utilized. The accuracy of the model’s core components is 98.1%, with specificity at 97% and sensitivity at 98.6%.
Emerging development in polymeric electrospun nanoscale mats for tissue regeneration: narrative review of the literature Hamza Abu Owida; Muhammad Al-Ayyad; Jamal Al-Nabulsi; Nidal Turab; Mustafa Abdullah
Bulletin of Electrical Engineering and Informatics Vol 12, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i5.4837

Abstract

Tissue engineering is a cutting-edge discipline that brings together scientific and health-related, biological, and engineering principles in order to build tissue-engineered constructions able to restore or sustain the physiological properties of native tissue, or to marginally enhance those properties. This field is called "regenerative medicine". By constructing structures that are analogous to the extracellular matrix, it will be possible to improve the transmission of oxygen and nutrients, as well as the release of toxins during the process of tissue healing, all while simultaneously maturing tissues. Over the past few years, various studies have concentrated on looking at nanostructures in three dimensions with the goal of using them in tissue engineering. In this group of methods, electrospinning stands out as one of the most successful options. Over the course of the past few decades, a great number of nanofibrous scaffolds have been produced for the purpose of restoring and repairing damaged tissue. In this article, the engineering of new tissues using nanofibrous textures as scaffolds are reviewed. In addition, recent developments in tissue regeneration and the difficulties related to electrospinning are discussed in this article, along with their respective solutions.
Available medical imaging modalities for melanoma screening Hamza Abu Owida; Muhammad Saleh Al-Ayyad; Jamal Al-Nabulsi; Nidal Turab
Indonesian Journal of Electrical Engineering and Computer Science Vol 34, No 1: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v34.i1.pp245-253

Abstract

The prevalence of melanoma of the skin has seen a significant rise in recent decades, constituting approximately one-third of all diagnosed cancer cases. Melanoma, the most fatal variant among cutaneous malignancies, exhibits a 4% probability of occurrence over an individual’s lifetime. The increasing incidence and mortality rates of skin cancer impose a substantial burden on healthcare resources and the economy. In recent years, several optical modalities, including dermoscopy, reflectance confocal microscopy (RCM), optical coherence tomography, multiphoton excited fluorescence imaging, and dermatofluorescence, have been extensively studied and utilized to improve the non-invasive diagnosis of skin cancer. This review article provides an analysis of the approach employed in the recently developed optical non-invasive diagnostic technologies. It explores the clinical uses of these techniques, while also examining their respective advantages and disadvantages. Furthermore, the paper explores the possibility for additional advancements in these technologies in the future.
Development of biomechanical behaviour of magnesium alloys for biomedical context Hamza Abu Owida; Feras Alnaimat; Bassam Al-Naami; Jamal Al-Nabulsi; Nidal Turab
Indonesian Journal of Electrical Engineering and Computer Science Vol 34, No 1: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v34.i1.pp98-108

Abstract

Magnesium alloys, which belong to the category of biodegradable metals, have a significant amount of potential to be utilized as implant materials, and as a result, they draw a lot of attention. This article is a review that summarizes the mechanical properties of magnesium alloys that are used in medical applications. This article illustrates the mechanical behaviors of magnesium alloys that are used in biomedical applications as well as the ways that may be used to improve the mechanical characteristics of biodegradable magnesium alloys. In conclusion, the difficulties that will need to be overcome in the creation of biodegradable magnesium alloys are discussed.
A comprehensive analysis of eye diseases and medical data classification Raed Alazaidah; Hamza Abu Owida; Nawaf Alshdaifat; Abedalhakeem Issa; Suhaila Abuowaida; Nidal Yousef
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 22, No 6: December 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v22i6.26058

Abstract

Vision loss is a critical health issue that presents substantial challenges to both individuals and communities. For those affected, it can lead to difficulties in performing daily activities, hinder educational and employment opportunities, and significantly impact mental health and overall quality of life. The inability to see can also lead to increased dependence on others, creating emotional and financial strains on families and caregivers. This paper highlights the benefit of machine learning (ML) in exploring conditions that significantly affect vision loss. The goals that will be achieved in this paper are to determine the best classifier capable of dealing with medical datasets and to determine the best strategy for dealing with medical data. Determine which feature selection is most applicable to use for examining medical data. Two medical datasets, 4 strategies, 19 classifiers, and 2 feature selections were used. As for the best classifier, the stochastic gradient descent (SGD) model was the best in dataset 1 and 2. The function strategy showed the best performance, followed by the rules strategy. CorrelationAttributeEval was shown to be the best feature selection, while ClassifierAttributeEval was the second-best feature selection.
Bridging ethics and performance in engineering education through predictive learning analytics Hamza Abu Owida; Areen Arabiat
International Journal of Evaluation and Research in Education (IJERE) Vol 15, No 4: August 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijere.v15i4.38767

Abstract

This literature review examines the opportunities, implementation challenges, ethical implications, and emerging directions of predictive learning analytics (PLA) in engineering education. Using a structured review of the literature, the study synthesizes evidence from several publications with emphasis on studies examining risk prediction, personalized support, curricular improvement, interpretability, fairness, and intervention design. The review shows that PLA can improve early identification of at-risk students, support adaptive learning pathways, and inform data-driven refinements in engineering curricula; however, its impact depends on data quality, model transparency, institutional capacity, and the availability of timely human support. The analysis further indicates that the most consequential barriers are fragmented data ecosystems, the difficulty of translating predictions into effective interventions, and unresolved ethical concerns related to privacy, bias, consent, and student agency. The article contributes to educational research by offering an integrated synthesis that connects technical development with pedagogical evaluation and ethical governance in engineering education. It concludes by proposing that future PLA adoption should align predictive modeling with explainable artificial intelligence, learning-theory-informed intervention design, and institution-level implementation strategies. Publications were selected for relevance to PLA in engineering education and then synthesized narratively across opportunities, challenges, ethics, and future directions.
Co-Authors Abdelqader Al-Maaiouf Abdullah Bleibel Abedalhakeem Issa Areen Arabiat Bassam Al-Naami Esraa Al-Aazeh Feras Alnaimat Hassan S. Migdadi Jamal Al-Nabulsi Jumana Ma’touq Muhammad Al-Ayyad Muhammad Saleh Al-Ayyad Mustafa Abdullah Nawaf Alshdaifat Nawaf Farhan Fankur Alshdaifat Nidal M. Turab Nidal Turab Nidal Yousef Omar Salah Mohamed Hemied Raed Alazaidah Rami S. Alkhawaldeh Sabrina Matar Suhaila Abuowaida Suhaila Farhan Ahmad Abuowaida