Nazar M Zaki

Nazar M Zaki
United Arab Emirates University | UAEU · College of Information Technology

B.Sc, M.Sc, Ph.D.
Professor of Computer Science (AI, Data Science), United Arab Emirates University

About

179
Publications
57,637
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
1,824
Citations
Citations since 2017
82 Research Items
1380 Citations
20172018201920202021202220230100200300400
20172018201920202021202220230100200300400
20172018201920202021202220230100200300400
20172018201920202021202220230100200300400
Introduction
Nazar Zaki is a Professor of Computer Science (AI and Machine-Learning). He served as a Chair, Department of Computer Science and Software Engineering, CIT, United Arab Emirates (UAEU) for almost 10 years introduced new academic programs and contributed significantly to the establishment and success of the department. Dr. Zaki is a founder and the Director of the Big Data Analytics Center at the United Arab Emirates University.
Additional affiliations
September 2012 - September 2015
United Arab Emirates University
Position
  • Infosphere: Semantic Web for Bioinformatics
Description
  • Funded by the ICT.
September 2011 - present
United Arab Emirates University
Position
  • Human Cancer Protein-Protein Interaction Network: Domain Linkers Perspective
Description
  • Funded by National Research Foundation.
February 2011 - present
United Arab Emirates University
Position
  • Glycomic Screen for Novel Molecular Therapeutic Targets: Insights into Saffron's Protection against Liver Cancer
Description
  • Funded by the National Research Foundation

Publications

Publications (179)
Article
Full-text available
Low Birth weight (LBW) infants pose a serious public health concern worldwide in both the short and long term for infants and their mothers. Infant weight prediction prior to birth can help to identify risk factors and reduce the risk of infant morbidity and mortality. Although many Machine Learning (ML) algorithms have been proposed for LBW predic...
Article
Full-text available
Precise classification of histopathological images is crucial to computer-aided diagnosis in clinical practice. Magnification-based learning networks have attracted considerable attention for their ability to improve performance in histopathological classification. However, the fusion of pyramids of histopathological images at different magnificati...
Article
Full-text available
Students’ emotional health is a major contributor to educational success. Hence, to support students’ success in online learning platforms, we contribute with the development of an analysis of the emotional orientations and triggers in their text messages. Such analysis could be automated and used for early detection of the emotional status of stud...
Preprint
Full-text available
Quality control and assurance plays a fundamental role within higher education contexts. One means by which quality control can be performed is by mapping the course learning outcomes (CLOs) to the program learning outcomes (PLO). This paper describes a system by which this mapping process can be automated and validated. The proposed AI-based syste...
Article
Full-text available
Blockchain technology has been extended from bitcoin transactions to applications in multiple domains. Scalability has been identified as a major challenge in large-scale blockchain networks because of the number of possible participants. Scalability becomes a consideration because the blockchain distributed ledger is replicated at all participatin...
Chapter
Cervical cancer is the most frequent cancer type among women worldwide and radiotherapy is the major clinical treatment. Organs in the radiation field are called Organ at Risks (OARs), which are prone to irreversible damage during radiotherapy. Therefore, accurate delineation of OARs is a critical step in ensuring radiotherapy dosimetry accuracy. H...
Article
Full-text available
Background: Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods:...
Article
Full-text available
Background Following the outbreak of COVID-19, several studies have reported that young adults encountered a rise in anxiety symptoms, which could negatively affect their quality of life. Promising evidence suggests that mobile apps with biofeedback, serious games, breathing exercises, and positive messaging, among other features, are useful for an...
Article
Full-text available
Accurate prediction of a newborn’s birth weight (BW) is a crucial determinant to evaluate the newborn’s health and safety. Infants with low BW (LBW) are at a higher risk of serious short- and long-term health outcomes. Over the past decade, machine learning (ML) techniques have shown a successful breakthrough in the field of medical diagnostics. Va...
Article
Full-text available
Background Hypoxia is a potentially life-threatening condition that can be seen in pneumonia patients.Objective We aimed to develop and test an automatic assessment of lung impairment in COVID-19 associated pneumonia with machine learning regression models that predict markers of respiratory and cardiovascular functioning from radiograms and lung C...
Article
Full-text available
Many high-demand industrial products are generated by microorganisms, including fuels, food, vitamins, and other chemicals. Metabolic engineering is the method of circumventing cellular control to manufacture a desirable product or to create a new product that the host cells do not normally need to produce. One of the objectives of microorganism me...
Article
Full-text available
Floods are among the devastating types of disasters in terms of human life, social and financial losses. Authoritative data from flood gauges are scarce in arid regions because of the specific type of dry climate that dysfunctions these measuring devices. Hence, social media data could be a useful tool in this case, where a wealth of information is...
Article
Full-text available
Background Dubai (United Arab Emirates; UAE) has a multi-national population which makes it exceptionally interesting study sample because of its unique demographic factors. Objective To stratify the risk factors for the multinational society of the UAE. Methods A retrospective chart review of 560 patients sequentially admitted to inpatient care...
Article
Full-text available
Automatic Speech Recognition (ASR) systems can be trained to achieve remarkable performance given large amounts of manually transcribed speech, but large labeled data sets can be difficult or expensive to acquire for all languages of interest. In this paper, we review the research literature to identify models and ideas that could lead to fully uns...
Chapter
The novel coronavirus (COVID-19) pandemic has spread rapidly worldwide infecting over 164.3 million people with approximately 3.4 million deaths. An automatic and fast diagnosis of COVID-19 in the earliest stage is crucial to further avoid its easy person-to-person transmission and deaths. Over the past decade, deep learning algorithms have shown i...
Article
Full-text available
Protein complexes are groups of two or more polypeptide chains that bind to form noncovalent networks of protein interactions. Over the past decade, researchers have created a number of means of computing the ways in which protein complexes and their members can be identified through these interaction networks. Although most of the existing methods...
Article
Full-text available
Background The human brain structure undergoes considerable changes throughout life. Cognitive function can be affected either negatively or positively. It is challenging to segregate normal brain aging from the accelerated one. Objective To work out a descriptive model of brain structural and functional changes in normal aging. Materials and Met...
Article
Full-text available
Background. Psychophysiological and cognitive tests as well as other functional studies can detect pre-symptomatic stages of dementia. When assembled with structural data, cognitive tests diagnose NDs more reliably thus becoming a multimodal diagnostic tool. Objective. Our main goal is to improve screening for dementia by studying an association be...
Article
Full-text available
Missing values are common in real-world datasets and pose a significant challenge to the performance of statistical and machine learning models. Generally, missing values are imputed using statistical methods, such as the mean, median, mode, or machine learning approaches. These approaches are limited to either numerical or categorical data. Imputa...
Article
Full-text available
Detecting at-risk students provides advanced benefits for reducing student retention rates, effective enrollment management, alumni engagement, targeted marketing improvement, and institutional effectiveness advancement. One of the success factors of educational institutes is based on accurate and timely identification and prioritization of the stu...
Article
Full-text available
Background: Neuroscience lacks a reliable method of screening the early stages of dementia. Objective: To improve the diagnostics of age-related cognitive functions by developing insight into the proportionality of age-related changes in cognitive subdomains. Materials and Methods: We composed a battery of psychophysiological tests and collected an...
Article
Full-text available
Educational Data Mining plays a critical role in advancing the learning environment by contributing state-of-the-art methods, techniques, and applications. The recent development provides valuable tools for understanding the student learning environment by exploring and utilizing educational data using machine learning and data mining techniques. M...
Preprint
Full-text available
Protein complexes are groups of two or more polypeptide chains that join together to build noncovalent networks of protein interactions. A number of means of computing the ways in which protein complexes and their members can be identified from these interaction networks have been created. While most of the existing methods identify protein complex...
Article
Alternative media has provided space for the disenfranchised, where counterhegemony and political practice can take place. Social media platforms have allowed for the formation of new communicative space that disrupts power structures and the established flow of information. This has allowed individuals, who share similar values and ideas, to come...
Article
Full-text available
Background: Neuronal reactions and cognitive processes slow down during aging. The onset, rate, and extent of changes vary considerably from individual to individual. Assessing the changes throughout the lifespan is a challenging task. No existing test covers all domains, and batteries of tests are administered. The best strategy is to study each f...
Preprint
Full-text available
Automatic Speech Recognition (ASR) systems can be trained to achieve remarkable performance given large amounts of manually transcribed speech, but large labeled data sets can be difficult or expensive to acquire for all languages of interest. In this paper, we review the research literature to identify models and ideas that could lead to fully uns...
Article
Background AI in healthcare has been recognized by both academia and industry in revolutionizing how healthcare services will be offered by healthcare service providers and perceived by all stakeholders. Objectives We aim to review recent tendencies in building AI applications for medicine and foster its further development by outlining obstacles....
Article
Full-text available
Chest radiography is a significant diagnostic tool used to detect diseases afflicting the chest. The automatic detection techniques associated with computer vision are being adopted in medical imaging research. Over the last decade, several remarkable advancements have been made in the field of medical diagnostics with the application of deep learn...
Article
Full-text available
Background A novel coronavirus (COVID-19) has taken the world by storm. The disease has spread very swiftly worldwide. A timely clue which includes the estimation of the incubation period among COVID-19 patients can allow governments and healthcare authorities to act accordingly. Objectives to undertake a review and critical appraisal of all publi...
Article
Full-text available
Background Despite the necessity, there is no reliable biomarker to predict disease severity and prognosis of patients with COVID-19. The currently published prediction models are not fully applicable to clinical use. Objectives To identify predictive biomarkers of COVID-19 severity and to justify their threshold values for the stratification of t...
Preprint
Full-text available
Neuroimaging data may reflect the mental status of both cognitively preserved individuals and patients with neurodegenerative diseases. To find the relationship between cognitive performance and the difference between predicted and observed functional test results, we developed a Convolutional Neural Network (CNN) based regression model to estimate...
Preprint
Full-text available
Chest radiography is an important diagnostic tool for chest-related diseases. Medical imaging research is currently embracing the automatic detection techniques used in computer vision. Over the past decade, Deep Learning techniques have shown an enormous breakthrough in the field of medical diagnostics. Various automated systems have been proposed...
Article
Full-text available
Background and aims To undertake a review and critical appraisal of published/preprint reports that offer methods of determining the effects of hypertension, diabetes, stroke, cancer, kidney issues, and high-cholesterol on COVID-19 disease severity. Methods A search was conducted by two authors independently on the freely available COVID-19 Open R...
Preprint
Full-text available
Background A novel form of coronavirus disease (SARS-CoV-2) has spread rapidly across the world. What risk factors influence the severity of the disease is of considerable importance. Aim This research offers a systematic review and meta-analysis of the correlation between common clinical conditions and comorbidities and the severity of COVID-19....
Preprint
Full-text available
Background: A novel form of coronavirus disease (SARS-CoV-2) has spread rapidly across the world. This disease, originating in Wuhan, China, has become a global pandemic. What risk factors influence the severity of the disease is of considerable importance. Aim: This research is intended to offer a systematic review/meta-analysis for assessing how...
Preprint
Full-text available
Background: A novel form of coronavirus disease (SARS-CoV-2) has spread rapidly across the world. What risk factors influence the severity of the disease is of considerable importance. Aim: This research offers a systematic review and meta-analysis of the correlation between common clinical conditions and comorbidities and the severity of COVID-19....
Preprint
Full-text available
Background: A novel form of coronavirus disease (SARS-CoV-2) has spread rapidly across the world. What risk factors influence the severity of the disease is of considerable importance. Objectives: This research offers a systematic review and meta-analysis of the correlation between common clinical conditions and comorbidities and the severity of CO...
Preprint
Full-text available
Objective: To undertake a review and critical appraisal of published/preprint reports that offer methods of determining the effects of hypertension, diabetes, stroke, cancer, kidney issues, and high-cholesterol on COVID-19 disease severity. Data sources: Google Scholar, PubMed, COVID-19 Open Research Dataset: a resource of over 128,000 scholarly ar...
Preprint
Full-text available
Objective: to undertake a review and critical appraisal of all published/preprint reports that offer an estimation of incubation periods for novel coronavirus (COVID-19). Design: a rapid and systematic review/critical appraisal Data sources: COVID-19 Open Research Dataset supplied by Georgetown's Centre for Security and Emerging Technology as well...
Chapter
The identification of protein complexes is becoming increasingly important to our understanding of cellular functionality. However, if a biologist wishes to investigate a certain protein, currently no method exists to assist him/her to accurately retrieve the possible protein partners that are expected to be in the same functional complex. Here, we...
Article
Full-text available
Clustering techniques can group genes based on similarity in biological functions. However, the drawback of using clustering techniques is the inability to identify an optimal number of potential clusters beforehand. Several existing optimization techniques can address the issue. Besides, clustering validation can predict the possible number of pot...
Chapter
Full-text available
Convolutional neural networks (CNNs) have recently achieved outstanding results for various vision tasks, including indoor scene understanding. The de facto practice employed by state-of-the-art indoor scene recognition approaches is to use RGB pixel values as input to CNN models that are trained on large amounts of labeled data (ImageNet or Places...
Book
Next-generation sequencing technologies, together with other emerging and quite diverse experimental techniques, are evolving rapidly, creating numerous types of omics data. These are creating new challenges for the expanding fields of bioinformatics and computational biology, which seek to analyze, process, integrate, and extract meaningful knowle...
Article
Nowadays, airline ticket prices can vary dynamically and significantly for the same flight, even for nearby seats within the same cabin. Customers are seeking to get the lowest price while airlines are trying to keep their overall revenue as high as possible and maximize their profit. Airlines use various kinds of computational techniques to increa...
Chapter
A large number of biological databases are currently in use by scientists. These databases employ different formats, many of which can be converted into resource description format (RDF), which can be subsequently queried using semantic web methods. These databases have “inter” and “intra” database relationships. RDF has an inherent graph structure...
Article
Full-text available
Organizations in many domains generate a considerable amount of heterogeneous data every day. Such data can be processed to enhance these organizations’ decisions in real time. However, storing and processing large and varied datasets (known as big data) is challenging to do in real time. In machine learning, streaming feature selection has always...
Article
Aim: Amyloid beta (Aβ) 1-42, which is a basic constituent of amyloid plaques, binds with extracellular transmembrane receptor nicotine acetylcholine receptor α7 (nAChRα7) in Alzheimer’s disease. Materials and Methods: In the current study, a computational approach was employed to explore the active binding sites of nAChRα7 through Aβ 1–42 interacti...