Big Data Analytics Center

Publications

  1. Nawaz, S. S. Khan and A. Ahmad, "Ensemble of Autoencoders for Anomaly Detection in Biomedical Data: A Narrative Review," in IEEE Access, vol. 12, pp. 17273-17289, 2024 
  2. A Ahmad, One-Class Classification by Ensembles of Random Planes (OCCERPs), Computational Intelligence and Neuroscience 2022.Workshop paper
  3. Najah Abu Ali, Mubashir Rehman, Shahid Mumtaz, Muhammad Bilal Khan, Mohammad Hayajneh, Farman Ullah Gul Rauf, Raza Ali Shah, “Contactless Diseases Diagnoses using Wireless Communication Sensing: Methods and Challenges Survey”, Computing Surveys, ACM, (Top 1%, Impact Factor: 16.6 (ranked 3/111 in Computer Science Theory & Methods), SJR 6.28)
  4. Najah AbuAli, Zulqurnain Sabir “Designing a heuristic computing structure to solve the human balancing model”, Journal of King Saud University-Computer and Information Sciences, Elsevier, 2024 (25%, SJR 1.2, IF 7.4)
  5. Bisni Fahad Mon, Mohammad Hayajneh, Najah Abu Ali, Farman Ullah, Hikmat Ullah Shayma Alkobaisi. 'Digital Twins in the IIoT: Current Practices and Future Directions toward Industry 5.0'. (Submitted in Journal- Internet of Things and Cyber-Physical Systems).
  6. Bisni Fahad Mon, Asma Wafi, Mohammad Hayajneh, Najah Abu Ali, Ahmad Slim, ‘Curriculum Complexity Evaluation Based on Course Cruciality’, In IEEE Global Engineering Education Conference (EDUCON) 2024 (Accepted & Presented)
  7. Ahmad Slim, Heileman, Al Yusuf, Yiming Zhang, Asma Wasfi, Mohammad Hajajneh, Bisni Fahad Mon, ‘Enhancing Academic Pathways: A Data-Driven Approach to Reducing Curriculum Complexity and Improving Graduation Rates in Higher Education’, In 2024 American Society for Engineering Education Annual Conference and Exposition (Accepted)
  8.  M.S. Aslam, H. Bilal, & M. Hayajneh, “Lqr-based PID controller with variable load tuned with data-driven methods for double inverted pendulum”, Soft Computing 28, 325–338 (2024). https://doi.org/10.1007/s00500-023-09442-9.
  9. S Al Ghazali, N Zaki, L Ali, S Harous.(2024). Exploring the potential of ChatGPT as a Substitute teacher: A Case Study. Int. J. Inf. Educ. Technol 14, 271-278
  10. I Ghebrehiwet, N Zaki, R Damseh, MS Mohamad.(2024). Revolutionizing Personalized Medicine with Generative AI: A Systematic Review. 24 January 2024, PREPRINT (Version 1) available at Research Square [https://doi.org/10.21203/rs.3.rs-3888891/v1]
  11. S Turaev, A Babu, S Al-Dabet, J Rustamov, Z Rustamov, N Zaki, et.al(2024). Data-Driven Analysis of Patients’ Body Language in Healthcare: A Comprehensive Review. IEEE Access
  12. R Sharma, H Abbastabar, DM Abdulah, H Abidi, H Abolhassani, et, al.(2024). Temporal patterns of cancer burden in Asia, 1990–2019: a systematic examination for the Global Burden of Disease 2019 study. The Lancet Regional Health-Southeast Asia 21.
  13. B Albreiki, Z Rustamov, J Rustamov, N Zaki.(2024). Enhancing Predictive Performance in Identifying At-Risk Students: Integration of Topological Features, Node Embeddings in Machine Learning Models. Machine Learning in Educational Sciences: Approaches, Applications and Advances.
  14. JD Steinmetz, KM Seeher, N Schiess, E Nichols, B Cao, C Servili, et.al.(2024). Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021 .The Lancet Neurology 23 (4), 344-381
  15. A Avan, VL Feigin, DA Bennett, JD Steinmetz, V Hachinski, S Stranges, et.al(2024). The burden of neurological conditions in north Africa and the Middle East, 1990–2019: a systematic analysis of the Global Burden of Disease Study 2019. The Lancet Global Health
  16. J Rustamov, Z Rustamov, MS Mohamad, N Zaki, A Al Tenaiji, M Al Harbi,et.al.(2024). An expert rule-based approach for identifying infantile-onset Pompe disease patients using retrospective electronic health records. 22 April 2024, PREPRINT (Version 1) available at Research Square [https://doi.org/10.21203/rs.3.rs-4262735/v1]
  17. AE Schumacher, HH Kyu, A Aali, C Abbafati, J Abbas, et,al.(2024). Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021. The Lancet 403 (10440), 1989-2056
  18. NV Bhattacharjee, AE Schumacher, A Aali, YH Abate, R Abbasgholizadeh, et,al.(2024). Global fertility in 204 countries and territories, 1950–2021, with forecasts to 2100: a comprehensive demographic analysis for the Global Burden of Disease Study 2021. The Lancet 403 (10440), 2057-2099.
  19. M Naghavi, KL Ong, A Aali, HS Ababneh, YH Abate, C Abbafati, et,al.(2024). Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021. The Lancet 403 (10440), 2100-2132
  20. AJ Ferrari, DF Santomauro, A Aali, YH Abate, C Abbafati, H Abbastabar,et,al.(2024). Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021. The Lancet 403 (10440), 2133-2161
  21. M Brauer, GA Roth, AY Aravkin, P Zheng, KH Abate, YH Abate, C Abbafati,et.al.(2024). Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021. The Lancet 403 (10440), 2162-2203
  22. SE Vollset, HS Ababneh, YH Abate, C Abbafati, R Abbasgholizadeh, et.al.(2024). Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021. The Lancet 403 (10440), 2204-2256.
  23. M Al Akasheh, O Hujran, EF Malik, N Zaki.(2024). Enhancing the Prediction of Employee Turnover with Knowledge Graphs and Explainable AI. IEEE Access
  24. N Zaki, A Krishnan, S Turaev, Z Rustamov, J Rustamov, A Almusalami,et.al.(2024). Node embedding approach for accurate detection of fake reviews: a graph-based machine learning approach with explainable AI. International Journal of Data Science and Analytics, 1-21
  25. MA Sharaf, H Helal, N Zaki, W Alketbi, L Alkaabi, S Alshamsi, F Alhefeiti.(2024). Automated Recommendation of Aggregate Visualizations for Crowdfunding Data. Algorithms 17 (6), 244.

  1. van der Haar,D., Moustafa,A., Warren,SL., Alashwal,H.. van Zyl, T. (2023). An Alzheimer’s disease category progression sub-grouping analysis using manifold learning on ADNI.  Scientific Reports 13 (1), 10483
  2. Alothali,E., Hayawi,K., Alashwal,H.(2023). SEBD: A Stream Evolving Bot Detection Framework with Application of PAC Learning Approach to Maintain Accuracy and Confidence Levels. Applied Sciences 13 (7), 4443
  3. Nawaz,A., Ahmad,A.(2023). Explainable Artificial Intelligence in Medical Diagnostics: Insights into Alzheimer's Disease, 6th Workshop on AI for Aging, Rehabilitation, and Intelligent Assisted Living (ARIAL) @ECML'23, September 18, 2023, ECML PKDD 2023, Torino, Italy
  4. AbuAli,N., Khan,M.B., Hayajneh,M., Rehman,M.(2023). Exploiting Wireless Communication Using Software-Defined Radio Frequency Sensing for E-Health Applications, IEEE Communications Standards Magazine, Accepted
  5. Ullah,F., AbuAli, N., Ullah, A., Ullah, R., Siddiqui, UA., Siddiqui, AA, “Fusion- Based Body-Worn IoT Sensor Platform for Gesture Recognition of Autism Spectrum Disorder Children”  Sensors 23 (3), 1672.
  6. Ullah,H., AbuAli,N., Hayajneh,M.(2023).A Digital Twin Framework for Personalized Healthcare Management Services,  IEEE 9th World Forum on Internet of Things (WF-IoT 2023), Aveiro, Portugal.
  7. Fahad Mon,B., Wasfi,A., Hayajneh,M.,  Slim, A.(2023). A Study on Role of Artificial Intelligence in Education. International Conference on Computing, Electronics and Communications Engineering, iCCECE 2023
  8. Fahad Mon, B., Wasfi, A., Hayajneh, M., Slim, A., & Abu Ali, N. (2023). Reinforcement Learning in Education: A Literature Review. Informatics, 10(3), 74. https://doi.org/10.3390/informatics10030074
  9. Asma Wasfi, Bisni Fahad Mon, Mohammad Hayajneh, Ahmad Slim, Najah Abu Ali, ‘Optimizing Assessment Placement and Curriculum Structure through Graph – Theoretic Analysis’, In 2023 15th International Conference on Innovations in Information Technology (IIT), pp. 93-97. IEEE, 2023.
  10. W Khan, N Zaki, A Ahmad, J Bian, L Ali, M Mehedy Masud, N Ghenimi.(2023). Infant low birth weight prediction using graph embedding features. International Journal of Environmental Research and Public Health 20 (2), 1317
  11. S Diao, W Luo, J Hou, R Lambo, HA Al-Kuhali, H Zhao, Y Tian, Y Xie.(2023).Deep multi-magnification similarity learning for histopathological image classification. IEEE Journal of Biomedical and Health Informatics 27 (3), 1535-1545
  12. Z Rustamov, J Rustamov, MS Sultana, J Ywei, V Balakrishnan, N Zaki.(2023). Cardiovascular Disease Prediction using Ensemble Learning Techniques: A Stacking Approach. 2023 19th IEEE International Colloquium on Signal Processing & Its …
  13. B Albreiki, T Habuza, N Zaki. (2023). Extracting topological features to identify at-risk students using machine learning and graph convolutional network models. International Journal of Educational Technology in Higher Education 20 (1), 23.
  14. J Rustamov, Z Rustamov, N Zaki. (2023). Green space quality analysis using machine learning approaches. Sustainability 15 (10), 7782
  15. S Turaev, S Al-Dabet, A Babu, Z Rustamov, J Rustamov, N Zaki. (2023). Review and analysis of patients’ body language from an artificial intelligence perspective. IEEE Access
  16. F Hashim, A Navaz, N Zaki, K Shuaib, MA Serhani. (2023). Artificial Intelligence and Blockchain-Based Trading Framework for Satellite Images. 2023 International Wireless Communications and Mobile Computing (IWCMC), 786-792
  17. Z Rustamov, J Rustamov, N Zaki, S Turaev, MS Sultana, JY Tan. (2023). Enhancing Cardiovascular Disease Prediction: A Domain Knowledge-Based Feature Selection and Stacked Ensemble Machine Learning Approach.26 June 2023, PREPRINT (Version 1) available at Research Square [https://doi.org/10.21203/rs.3.rs-3068941/v1]
  18. N Zaki, H Singh, LC Kiong, N Zaki, S Alnuaimi. (2023). Real-Time Population Density Estimation in Dubai Through Deep Learning and Car Counting in Satellite Images. 2023 International Conference on Machine Learning and Cybernetics (ICMLC).
  19. S Azadnajafabad, S Saeedi Moghaddam, E Mohammadi, N Rezaei. (2023). Burden of breast cancer and attributable risk factors in the North Africa and Middle East region, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. Frontiers in Oncology 13, 1132816.
  20. B Albreiki, T Habuza, N Palakkal, N Zaki. (2023). Clustering-based knowledge graphs and entity-relation representation improves the detection of at risk students. Education and Information Technologies, 1-30
  21. N Zaki, W Qin, A Krishnan. (2023). Graph-based methods for cervical cancer segmentation: Advancements, limitations, and future directions. AI Open
  22. M Al Akasheh, EF Malik, O Hujran, N Zaki. (2023). A Decade of Research on Data Mining Techniques for Predicting Employee Turnover: A Systematic Literature Review. Expert Systems with Applications, 121794.
  23. W Qin, N Zaki, F Zhang, J Wu, F Yang, C Li. (2023). Computational Mathematics Modeling in Cancer Analysis: Second International Workshop, CMMCA 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023. Springer Nature
  24. B Zheng, J He, J Zhu, Y Xie, N Zaki, W Qin. (2023).Style Enhanced Domain Adaptation Neural Network for Cross-Modality Cervical Tumor Segmentation. International Workshop on Computational Mathematics Modeling in Cancer Analysis.
  25. W Khan, N Zaki, A Ahmad, MM Masud, R Govender, N Rojas-Perilla, L Ali. (2023). Node embedding-based graph autoencoder outlier detection for adverse pregnancy outcomes. Scientific reports 13 (1), 19817
  26. AM ElMassry, A Alshamsi, AF Abdulhameed, MA Sharaf, N Zaki. (2023). A Regression Analysis Approach for Feature Selection in Student Achievement Data. 2023 15th International Conference on Innovations in Information Technology.
  27. N Zaki, H Singh, A Krishnan, A Alnaqbi, S Alneyadi, S Alnaqbi. (2023). Transfer Learning and Explainable Artificial Intelligence Enhance the Classification of Date Fruit Varieties. 2023 15th International Conference on Innovations in Information Technology.
  28. N Zaki, S Turaev, K Shuaib, A Krishnan, E Mohamed. (2023). Automating the mapping of course learning outcomes to program learning outcomes using natural language processing for accurate educational program evaluation. Education and Information Technologies 28 (12), 16723-16742
  29. D Smetanina, T Habuza, N Zaki, D Qandil, F Ismail, M Ljubisavljevic.(2023). Prognostication of MCI-to-dementia conversion with recently proposed marker “deviation from model of normal ageing”. Journal of the Neurological Sciences 455.
  30. N Kuznetsov, T Habuza, N Zaki, M Ljubisavljevic, F Ismail, D Qandil.et, al.(2023). Differentiation between Alzheimer's and non-Alzheimer’dementia with recently proposed marker “deviation from model of normal ageing”. Journal of the Neurological Sciences 455
  31. W Khan, N Zaki, N Ghenimi, A Ahmad, J Bian, MM Masud, N Ali, et.al (2023). Predicting preterm birth using explainable machine learning in a prospective cohort of nulliparous and multiparous pregnant women. Plos one 18 (12), e0293925

  1. AlDarmaki,H., , Asad Ullah,S., Zaki,N. (Accepted) vised Automatic Speech Recognition : A Review. Speech Communication. (Q1)
  2. Statsenko, Y., Habuza, T., Smetanina, D., Simiyu,G., Uzianbaeva,L.n., Gorkom,K., Zaki,N., et al.(2022). Brain morphometry and cognitive performance in normal brain aging: age- and sex-related structural and functional changes. Frontiers in Aging Neuroscience (Q1)
  3. Dankar, F., Mahmoud K. I., Ismail, L. (2022). A Multi-Dimensional Evaluation of Synthetic Data Generators. IEEE Access. (Q1)
  4. Amanat ,Ali, Soman, S., Vijayan,R. (2022) Dynamics of camel and human hemoglobin revealed by molecular simulations. Scientific Reports 12(1):122. Pubmed ID: 34997093. DOI: 10.1038/s41598-021-04112-y (Q1)
  5. Al Zahmi, F., Habuza, T., Awawdeh, R., Elshekhali, H., Lee, M., Salamin, N., Sajid R, Kiran D., Nihalani S., Smetanina D., Talako T.,  Gorkom NV., Zaki N., Statsenko, Y. (2022). Ethnicity-Specific Features of COVID-19 Among Arabs, Africans, South Asians, East Asians, and Caucasians in the United Arab Emirates. Frontiers in Cellular and Infection Microbiology, 1241. (Q1)
  6. Statsenko, Y., Al Zahmi, F., Habuza, T., Almansoori, T. M., Smetanina, D., Simiyu, G. L.,Al Koteesh, J. (2022). Impact of Age and Sex on COVID-19 Severity Assessed from Radiologic and Clinical Findings. Frontiers in cellular and infection microbiology, 1395. (Q1)
  7. Farhad, M., Mohamad, M.S., Beg, A. (2022). Deep Learning Based Cardiac Phase Detection Using Echocardiography Imaging. International Conference on Advanced Data Mining and Applications. Springer, Cham.
  8.  Mohamad, M.S., Hayawi, K., Mathew, S.S., Michael, T., El Barachi, M. (2022). Smart Online Exam Proctoring Assist for Cheating Detection. International Conference on Advanced Data Mining and Applications. Springer, Cham.
  9. Das, S.S., Shanto, S., Rahman, M., Islam, M.S., Rahman, A., Mohamad, M.S., Ali. (2022). BayesBeat: Reliable Atrial Fibrillation Detection from Noisy Photoplethysmography Data. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies. ACM New York, NY, USA. Vol.6. (Q1)
  10. Habuza,T., Zaki,N., Mohamed, EA., Statsenko, Y.(2022). Deviation From Model of Normal Aging in Alzheimer’s disease: Application of Deep Learning to Structural MRI data and Cognitive Tests. IEEE Access (Q1)
  11. Khan,Q., Kalbus, E., Zaki, N., Mohamed, MM.(2022). Utilization of social media in floods assessment using data mining techniques.PLos one 17 (4), e0267079 (Q1)
  12. Khan, W., Zaki, N.(2022). COVID-19 Detection from Chest X-ray Using Deep Learning Ensemble Classifier. Data Intelligence and Cognitive Informatics, 429-441
  13. CB Tan, MHA Hijazi, K Frazier, MS Mohamad, PNE Nohuddin(2022). Artificial speech detection using image-based features and random forest classifier. IAES International Journal of Artificial Intelligence 11 (1), 161 (Q3)
  14. P Dehghan, H Alashwal, AA Moustafa.(2022). Applications of machine learning to behavioral sciences: focus on categorical data. Discover Psychology 2 (1), 1-10
  15. M Hassan, MS Iqbal, S Naqvi, H Alashwal, AA Moustafa, A Kloczkowski.(2022). Prediction of site directed miRNAs as key players of transcriptional regulators against influenza C virus infection through computational approaches. Frontiers in molecular biosciences, 340 (Q1)
  16. F Faghihi, H Alashwal, AA Moustafa.(2022). A Synaptic Pruning-Based Spiking Neural Network for Hand-Written Digits Classification. Frontiers in Artificial Intelligence, 12 (Q4) 
  17. H Alashwal, M El Halaby, JJ Crouse, A Abdalla, AA Moustafa.(2022). The Application of Unsupervised Clustering Methods to Alzheimer’s. Frontiers in Computational Neuroscience–Editors’ Pick 2021 (Q2)
  18. Y Statsenko, T Habuza, E Fursa, A Ponomareva, TM Almansoori.(2022). Prognostication of incidence and severity of ischemic stroke in hot dry climate from environmental and non-environmental predictors. IEEE Access (Q1)
  19. Alothali,E., Hayawi,K., Alashwal,H.(2022). Using Self-labeling and Co-Training to Enhance Bots Labeling in Twitter. 2022 IEEE/ACS 19th International Conference on Computer Systems and..
  20. Dzulkalnine,MF., Mohamad,Ms., Choon, YW., Remli, MA., Alashwal,H.(2022). Optimizing Ethanol Production in Escherichia Coli Using a Hybrid of Particle Swarm Optimization and Artificial Bee Colony. Proceedings of the 6th International Conference on Advances in Artificial …
  21. Alothali,E.,Salih,M., Hayawi,K., Alashwal,H.(2022). Bot-MGAT: A Transfer Learning Model Based on a Multi-View Graph Attention Network to Detect Social Bots. Applied Sciences 12 (16), 8117
  22. Faghihi., Cai,S., Moustafa,A.,  Alashwal,H.(2022). A Nonsynaptic Memory Based Neural Network for Hand-Written Digit Classification Using an Explainable Feature Extraction Method.Proceedings of the 6th International Conference on Information System and …
  23. Ahmad,A.,(2022). One-Class Classification by Ensembles of Random Planes (OCCERPs), Computational Intelligence and Neuroscience 2022
  24. Ayoub, Shahnawaz, Yonis Gulzar, Faheem Ahmad Reegu, and Sherzod Turaev. (2022). Generating Image Captions Using Bahdanau Attention Mechanism and Transfer Learning.Symmetry 14, no. 12: 2681. https://doi.org/10.3390/sym14122681 [Impact Factor: 2.7, SCOPUS Q1 (10%)]

  1. Statsenko, Y., Al Zahmi, F., Habuza, T., Gorkom, K. N. V., Zaki, N. (2021). Prediction of COVID-19 severity using laboratory findings on admission: informative values, thresholds, ML model performance. BMJ open, 11(2), e044500. (Q1)
  2. Statsenko, Y., Habuza, T., Charykova, I., Gorkom, K. N. V., Zaki, N., Almansoori, T. M., Belghali, M. (2021). Predicting age from behavioral test performance for screening early onset of cognitive decline. Frontiers in Aging Neuroscience, 282. (Q1)
  3. Al Breiki,B., Habuza,T., Shuqfa,Z., Serhani,M., Zaki,N., Harous,S. (2021) Customized Rule-Based Model to Identify At-risk Students and Propose Rational Remedial Actions. Big Data and Cognitive Computing. Big Data Cogn. Comput. 2021, 5(4), 71.(Q1)
  4. Statsenko,Y., Habuza,T.,  Gorkom, K. N. V., Zaki,N.,  Almansoori,T.M., Al Zahmi,F., Ljubisavljevic,M., Belghali,M.(2021). Proportional changes in cognitive subdomains during normal brain aging. Aging Neurosci. (Q1)
  5. Zaki,N., Singh,H., Mohamed, E. A.  (2021) Identifying Protein Complexes in Protein-Protein Interaction Data Using Graph Convolutional Network. IEEE Access, vol. 9, pp. 123717-123726, 2021, doi: 10.1109/ACCESS.2021.3110845. (Q1)
  6. AlBreiki,B., Zaki,N., Al Ashwal,H. (2021) A Systematic Literature Review of Student Performance Prediction Using Machine Learning Techniques. Educ. Sci. 2021, 11(9), 552. (Q1)
  7. Alsamri, M.T., Alabdouli, A., Iram, D., Alkalbani, A.M., Almarzooqi, A.S., Souid, A.-K., and Vijayan R. (2021) A study on the genetics of primary ciliary dyskinesia. Journal of Clinical Medicine 10(21):5102. PMID: 34768622. (Q1)
  8. Zaki,N., Elfadil, M. (2021) The Estimations of the COVID-19 Incubation Period: A Scoping Reviews of the Literature. J. of Infection and Public Health. 14(5):638-646. (Q1)
  9. Awang, T., Chairatana,P., Vijayan, R., Pongprayoon, P. (2021). Evaluation of the binding mechanism of human defensin 5 in a bacterial membrane: A simulation study. International Journal of Molecular Sciences. 22(22):12401. (Q1)
  10. Bashri, M., Zaki, N. (2021). #Allhandsondeck Shaun King and unite the right rally: mobilization and the networked social journalist. Atlantic Journal of Communication, 1-20. (Q2)
  11. Chamoso, P., Rodriguez, S., Mohamad, M.S., González-Briones, A. (2021). Bioinformatics Applications Based on Machine Learning. MDPI. Switzerland. ISBN: 978-3-0365-0761-3. This book is a printed edition of the Special Issue Bioinformatics Applications Based On Machine Learning that was published in Processes.
  12. Ching, S.C., Wen, L.J., Ismail, N.I.M., Looi, I., Kooi, C.W., Peng, L.S., Mui, L.S., Tamibmaniam, J., Muninathan, P., Hooi, O.B., Ali, S.M.D., Hassan, M.R.A.  Mohamad, M.S., Griffiths, L.R., Wei, L.K. (2021).  SLC17A3 rs9379800 and Ischemic Stroke Susceptibility at the Northern Region of Malaysia. Journal of Stroke and Cerebrovascular Diseases, pp. 105908, Elsevier.(Q1)Habuza, T., Navaz, A. N., Hashim, F., Alnajjar, F., Zaki, N., Serhani, M. A., Statsenko, Y. (2021). AI applications in robotics, precision medicine, and medical image analysis: an overview and future trends. Informatics in Medicine Unlocked, 100596. Vol. 24, 100596.(Q2)Jobe, A., Vijayan, R. (2021). Characterization of peptide binding to the SARS-CoV-2 host factor neuropilin. Heliyon 7(10): e08251. PMID: 34722943. (Q1)Khan, W., Zaki, N., Luqman, A. (2021). Intelligent Pneumonia Identification from Chest X-Rays: A Systematic Literature Review. IEEE Access. Vol 9, pp: 51747-51771, 2169-3536. (Q1)Man, M.Y., Mohamad, M.S., Choon, Y.W., Ismail. M.A. (2021). In silico gene knockout prediction using a hybrid of Bat algorithm and minimization of metabolic adjustment. Journal of Integrative Bioinformatics. pp. 20200037, De Gruyter. (Q1)Mazlan, A.U., Sahabudin, N.A., Remli, M.A., Ismail, N.S.N., Mohamad, M.S. (2021). A Review on Recent Progress in Machine Learning and Deep Learning Methods for Cancer Classification on Gene Expression Data. Processes. Vol. 9, No. 8, pp. 1466, MDPI. Mazlan, A.U., Sahabudin, N.A., Remli, M.A., Ismail, N.S.N., Mohamad, M.S., Warif. N.B.A.  (2021). Supervised and Unsupervised Machine Learning for Cancer Classification: Recent Development, 2021 IEEE International Conference on Automatic Control & Intelligent Systems (I2CACIS), pp. 392-395, Shah Alam, Malaysia, 26 June 2021. (conference)Mohamed, A.S, Humaira, E. (2021). Scalable Query Refinement for View Recommendation in Visual Data Exploration. IEEE Access. (Q1)Nies, H.W., Mohamad, M.S., Zakaria, Z., Chan, W.H., Remli, M.A., Nies, Y.H. (2021). Enhanced Directed Random Walk for the Identification of Breast Cancer Prognostic Markers from Multiclass Expression Data. Entropy. Vol. 23, No.9, pp. 1232, MDPI. (Q2)Ranjit, V. (2021) Teaching and learning during the COVID-19 pandemic: A topic modeling study. Education Sciences. 11(7):347. DOI: 10.3390/educsci11070347. (Q2)Rocha, M., Fdez-Riverola, F., Mohamad, M.S., Casado-Vara, R.  (2021). Practical Applications of Computational Biology & Bioinformatics. Springer. ISBN: 978-3-030-86258-9.Taleb, I., Serhani, M.A., Bouhaddioui, C. et al. (2021). Big data quality framework: a holistic approach to continuous quality management. J Big Data. 8, 76. (Q1)Xiaozhong, Z., Xiaoyu, G., Panos, K. C., Mohamed, A. S. (2021). ViewSeeker: An Interactive View Recommendation Framework. Big Data Research Journal. Vol. 25, 100238.(Q1)Yee, S.S., Mohamad, M.S., Choon, Y.W., Remli, M.A. (2021). An Enhancement of Succinate and Lactate Production Using a Hybrid of Bacterial Optimization Algorithm, International Conference on Emerging Technologies and Intelligent Systems (ICETIS 2021), Pahang, Malaysia. 25-26 June 2021. (conference)
  13. Dankar, Fi., Ibrahim, M. (2021). Fake It Till You Make It: Guidelines for Effective Synthetic Data Generation. Applied Sciences 11.5: 2158. (Q2)
  14. Yong, M.I., Mohamad, M.S., Choon, Y.W., Chan, W.H., Adli, H.K., Syazwan, K.N., Yusoff, N. , Remli, M.A. (2021). A Hybrid of Bees Algorithm and Regulatory On/Off Minimization for Optimizing Lactate Production. The 15th International Conference on Practical Applications of Computational Biology Bioinformatics (PACBB), pp. 95-104, Salamanca, Spain, 6-8 October 2021. (conference)Zaki,N., Mohamed,EA., Habuza,T. (2021). From Tabulated Data to Knowledge Graph: A Novel Way of Improving the Performance of the Classification Models in the Healthcare Data. medRxiv.
  15. A.A ,Arabi.(2021). Artificial intelligence in drug design: algorithms, applications, challenges and ethics. Future Drug Discovery 3 (2), FDD59
  16. Y Statsenko, E Fursa, V Laver, N Altakarli, T Almansoori, F Al Zahmi.(2021). Risk stratification and prediction of severity of hemorrhagic stroke in dry desert climate-a retrospective cohort study in eastern region of Abu Dhabi Emirate. Journal of the neurological sciences 429 (Q2)
  17. Y Statsenko, E Fursa, V Laver, N Altakarli, T Almansoori, F Al Zahmi.(2021). Prediction of early functional outcomes of hemorrhagic stroke. Journal of the Neurological Sciences 429 (Q2)
  18. E Alothali, K Hayawi, H Alashwal.(2021). Hybrid feature selection approach to identify optimal features of profile metadata to detect social bots in Twitter. Social Network Analysis and Mining 11 (1), 1-15 (Q1)
  19. K Hayawi, S Shahriar, MA Serhani, H Alashwal, MM Masud.(2021). Vaccine versus Variants (3Vs): are the COVID-19 vaccines effective against the variants? A systematic review. Vaccines 9 (11), 1305 (Q1)
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Nov 27, 2024