EL Moudden, Ismail
- Biostatistician & Data Scientist, Healthcare Analytics & Delivery Science Institute
Overview
overview
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Dr. Ismail El Moudden is an Assistant Professor at Eastern Virginia Medical School (EVMS). He received his Ph.D. in statistics and data science after receiving his M.S in applied mathematics from the Mohammed V University in Rabat, Morocco. Prior to joining EVMS, he was at Mohammed V University, where he taught graduate level courses on applied mathematics and statistics. He also served as a visiting professor of data sciences at the International Academy Mohammed VI of Civil Aviation. As a Data Scientist and Biostatistician at the EVMS-Sentara Healthcare Analytics and Delivery Science Institute (HADSI), he ensures a rigorous, scientific evidence base for rapid-cycle health disparity research to increase the reach, external validity, and sustainment of effective cancer control and prevention interventions for the Cancer Health Disparities Outreach Program.
Dr. El Moudden has an active and continuing research agenda, he has publications representing a well-balanced array of research in statistical learning. His primary research includes Healthcare Analytics, and as PI or co-Investigator on several research projects, he has laid the groundwork of developing effective feature selection and extraction using parsimonious factors and shrinkage methods. He works closely with collaborators in the fields of cancer, heart disease, neurology, surgery, and social determinants of health. Dr. EL Moudden's research focuses on statistical methods for analysis of electronic health records, high-dimensional data modeling, machine learning, prognostic modeling, correlated data, competing risks with applications to healthcare delivery and outcomes research.
Publications
selected publications
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2022Is Anti-NXP2 Autoantibody a Risk Factor for Calcinosis and Poor Outcome in Juvenile Dermatomyositis Patients? Case Series. FRONTIERS IN PEDIATRICS. 9.Full Text via DOI: 10.3389/fped.2021.810785 PMID: 35280444
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2021A Hybrid Gene Selection Strategy Based on Fisher and Ant Colony Optimization Algorithm for Breast Cancer Classification. INTERNATIONAL JOURNAL OF ONLINE AND BIOMEDICAL ENGINEERING. 17:148-163.Full Text via DOI: 10.3991/ijoe.v17i02.19889
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2021A NOVEL DIMENSIONALITY REDUCTION APPROACH TO IMPROVE MICROARRAY DATA CLASSIFICATION. IIUM ENGINEERING JOURNAL. 22:1-23.Full Text via DOI: 10.31436/iiumej.v22i1.1447
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2021Assessment of the Banff Working Group classification of definitive BK polyomavirus nephropathy. TRANSPLANT INTERNATIONAL. tri.14003.Full Text via DOI: 10.1111/tri.14003
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2021Gene Selection for Cancer Classification: A New Hybrid Filter-C5.0 Approach for Breast Cancer Risk Prediction. Advances in Science, Technology and Engineering Systems Journal. 6:871-878.Full Text via DOI: 10.25046/aj060196
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2021Neuropathogenesis of Multiple Sclerosis and Huntington's Disease. Research Anthology on Diagnosing and Treating Neurocognitive Disorders. 59-78.Full Text via DOI: 10.4018/978-1-7998-3441-0.ch004
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2020Decision Tree Model Based Gene Selection and Classification for Breast Cancer Risk Prediction. Communications in Computer and Information Science. 165-177.Full Text via DOI: 10.1007/978-3-030-45183-7_12
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2019Neuropathogenesis of Multiple Sclerosis and Huntington's Disease. Advances in Environmental Engineering and Green Technologies. 266-285.Full Text via DOI: 10.4018/978-1-5225-7775-1.ch013
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2018Learned Model For Human Activity Recognition Based On Dimensionality Reduction. The 2nd International Conference on Smart Applications and Data Analysis for Smart Cities.
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2018Mining Prostate Cancer Behavior Using Parsimonious Factors and Shrinkage Methods. The 2nd International Conference on Smart Applications and Data Analysis for Smart Cities.
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2016Modeling Human Activity Recognition by Dimensionality Reduction Approach. Proceedings of the 27th International Business Information Management Association Conference Innovation Management and Education Excellence Vision 2020.
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2016Mining human activity using dimensionality reduction and pattern recognition. Contemporary Engineering Sciences. 9:1031-1041.Full Text via DOI: 10.12988/ces.2016.67119
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2016Modeling Human Behavior Using Feature Extraction and Class PredictionFull Text via DOI: 10.1109/cse-euc-dcabes.2016.227
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2015A Dimensionality Reduction Framework for Automatic Speech Recognition. Proceedings of the 26th International Business Information Management Association Conference Innovation Management and Sustainable Economic Competitive Advantage.
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2015Initial Model Selection for the Baum-Welch Algorithm Applied to Credit Scoring. Advances in Intelligent Systems and Computing. 359-368.Full Text via DOI: 10.1007/978-3-319-18167-7_31
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2014Learning Decision by Hidden Markov Model. Proceedings of the 24th International Business Information Management Association Conference - Creating Global Competitive Economies: 2020 Vision Strategic Planning and Smart Implementation.
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2014Classification with hidden Markov model. Applied Mathematical Sciences. 8:2483-2496.Full Text via DOI: 10.12988/ams.2014.42129
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Feature selection and extraction for class prediction in dysphonia measures analysis:A case study on Parkinson’s disease speech rehabilitation. Technology and Health Care. 25:693-708.Full Text via DOI: 10.3233/thc-170824
Research
research overview
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Dr. EL Moudden research interests lie at the forefront of modeling, analysis, and classification of large-scale data based on dimensionality reduction methods using Machine Learning, Deep Learning and AI techniques. He has pursued a set of integrated activities for research, teaching, and service in the area of Biostatistics and Data Science. With his background in Statistics and Data Science, his goal is to integrate Machine Learning, Deep Learning and AI techniques with clinical research. The idea of precision medicine is of growing interest among scientific researchers and healthcare providers. During my time here, I have supported some clinical projects with about 5% of these studies assessing how these techniques can simplify the lives of patients, doctors, and hospital administrators by performing tasks that are typically done by humans, but in less time and at a fraction of the cost. Therefore, I would like to contribute to the expansion of this type of research; I believe this more novel type of research would be very beneficial to the research community and help strengthen the research culture as a whole.
Contact
full name
- Ismail EL Moudden