Dr Mohammed Baragilly BSc, MSc, PhD

Dr Mohammed Baragilly

Institute of Inflammation and Ageing
Research Fellow
Honorary Research Fellow – Medical Statistics, Institute of Applied Health Research

Contact details

Telephone
+44 (0)121 414 3477
Email
m.h.h.baragilly@bham.ac.uk
View my research portal
Address
University of Birmingham Research Laboratories
Queen Elizabeth Hospital
Institute of Inflammation and Ageing
University of Birmingham
Edgbaston
Birmingham
B15 2TT
UK

Mohammed Baragilly is a Research Fellow based at the Institute of Inflammation and Ageing and holds an Honorary Research Fellowship in medical statistics at the Institute of Applied Health Research, University of Birmingham. Additionally, he serves as an Assistant Professor of Statistics in the Department of Mathematics, Insurance and Applied Statistics at Helwan University, Egypt.

With a rich history of diverse projects and roles within the College of Medical and Dental Sciences, Mohammed has contributed to initiatives at the Institute of Applied Health Research, Institute of Immunology and Immunotherapy, and Institute of Inflammation and Ageing. His academic journey includes positions as a Teaching Assistant at the School of Mathematics and as a Statistical Consultant and tutor at the Mathematics Support Centre within the Academic Skills Centre at the University of Birmingham.

Driven by a keen interest in various statistical research domains, Mohammed has made significant contributions to Clustering Analysis, Constrained Models for Meta-Analysis of Diagnostic Test Accuracy, Image Comparisons based on similarity measures, Functional Data Analysis, Machine Learning Medical Applications, and Numerical Nonlinear Optimization for Estimating Bivariate Random Effects Models. His current focus lies in proposing innovative machine learning predictive models for medication error detection.

Qualifications

  1. PhD in Statistics, School of Mathematics, University of Birmingham, 2016.
  2. M.Res. in Statistics, School of Mathematics, University of Birmingham, 2014.
  3. M.Sc. in Statistics, Department of Mathematics and Applied Statistics, Helwan University, 2009.
  4. B.Sc. in Applied Statistics, Department of Mathematics and Applied Statistics, Helwan University, 2004.

Biography

Mohammed earned his Doctor of Philosophy in Statistics from the School of Mathematics at the University of Birmingham in 2016. His doctoral research delved into clustering multivariate and functional data, employing non-parametric methods.

Post-PhD, he embarked on a role as a Research Fellow in Medical Statistics within the Department of Primary Care Clinical Sciences at the Institute of Applied Health Research, University of Birmingham, starting in 2016.

Throughout his career, Mohammed has demonstrated a prolific output, contributing to numerous research papers spanning areas such as clustering analysis for multivariate and functional data, constrained models for meta-analysis of diagnostic test accuracy, image comparisons based on similarity measures, and numerical nonlinear optimization for bivariate random effects models. These impactful papers have found a home in esteemed journals, including Nature Methods, Statistical Methods in Medical Research, BMC Medical Research Methodology, British Journal of General Practice, and Journal of Clinical Epidemiology.

Currently, Mohammed is actively engaged in a project at the Institute of Inflammation and Ageing, focusing on the development and testing of novel clinical decision support tools. This project utilizes electronic health data from PIONEER, the HDR UK Hub in acute care, aiming to enhance patient outcomes by mitigating errors in prescriptions and identifying potential drug-drug interactions.

Teaching

Previous Teaching:

(1) School of Mathematics, University of Birmingham (2012 – 2016):

  • Applied Statistics
  • Discrete Mathematics
  • Introductory Mathematics
  • Further Mathematics
  • Discrete Mathematics and Statistics
  • Probability and Statistics
  • Statistics 2
  • Statistical Methods in Economics

(2) Department of Mathematics and Applied Statistics, Helwan University (2004-2012):

  • Applied Statistics 
  • Statistics 1
  • Introductory Mathematics
  • Financial and Investment Mathematics
  • Mathematical Statistics (1&2)
  • Mathematics for Business Information Systems
  • Operations Research
  • Insurance and its Applications
  • Statistical Laboratory (SPSS, Tora and Maple)

Research

  1. Machine learning predictive models.
  2. Image comparisons based on similarity measures.
  3. Constrained models for diagnostic test accuracy;
  4. Numerical nonlinear optimization;
  5. Tailored meta-analysis;
  6. Multivariate nonparametric statistical methods;
  7. Clustering analysis for the multivariate data;
  8. Functional data clustering.

Other activities

Conference (contributed & invited) Presentations:

  1. “Determining the number of clusters using multivariate ranks” in the International Conference on Robust Statistics (ICORS 2015 that has been held at the Indian Statistical Institute, Kolkata, India during January 12 - 16, 2015).
  2. “Clustering Multivariate Data Using Central Rank Regions” in the Multivariate Analysis Today: Topical Expository Reviews (MATTER 2015 that has been held at Faculty of Mathematics, Computing and Technology, Department of Mathematics and Statistics, The Open University, UK 20 May 2015).
  3. “Clustering Multivariate Data Using Weighted Spatial Ranks” in the International Conference (DAGStat 2016: Fourth Joint Statistical Meeting of the Deutsche Arbeitsgemeinschaft Statistik "Statistics under one Umbrella" at Gorge-August University,Göttingen, Germany).

  4. “Theoretical and Practical Investigation of Maximum Product of Spacings (MPS) Estimators” in the Euro-American Conference for Academic Disciplines 2015 – Paris, France (by The International Journal of Arts and Sciences IJAS).

  5. “Probabilistic Mortality Rate Function for Older Population” in the poster session of The Euro-American Conference for Academic Disciplines 2015 – Paris, France (by The International Journal of Arts and Sciences IJAS).

  6. “Measuring poverty among the aged” in the poster session of The Euro-American Conference for Academic Disciplines 2015 – Paris, France (by The International Journal of Arts and Sciences IJAS).

  7. “The effects of correlation between the test positive rate and prevalence on tailored meta-analysis” in the Diagnostic and Prognostic Research. Utrecht, The Netherlands. 2-3 July 2018; 2 (Supplement 1), 12, O37. “Estimating the parameters to a bivariate random-effects model in test accuracy meta-analysis using standard approaches” in the 25th Cochrane Colloquium, Edinburgh, UK. Cochrane Database of Systematic Reviews 2018;(9 Suppl 1).

  8. “Estimating the parameters to a bivariate random-effects model in test accuracy meta-analysis using standard approaches” in the 25th Cochrane Colloquium, Edinburgh, UK. Cochrane Database of Systematic Reviews 2018;(9 Suppl 1).

  9. “A meta-analysis over multiple thresholds to compare two prediction rules for acute pharyngitis” in 2020 SW SAPC Bristol Society for Academic Primary Care, Bristol, UK.

Publications

  1. Nieves, D.J., Pike, J.A., Levet, F., Williamson, D.J., Baragilly, M., Oloketuyi, S., de Marco, A., Griffié, J., Sage, D., Cohen, E.A.K., Sibarita, J-B., Heilemann, M., Owen, D.M. (2023). A framework for evaluating the performance of SMLM cluster analysis algorithms. Nature Methods. 20, 259-267. http://dx.doi.org/10.1038/s41592-022-01750-6.
  2. Baragilly M., Gabr, H. and Willis, B. H. (2023). Clustering analysis of multivariate data: a weighted spatial ranks-based approach. Journal of Probability and Statistics. https://doi.org/10.1155/2023/8849404.
  3. Baragilly, M. and Willis, B.H.(2022). Optimising a coordinate ascent algorithm for the meta-analysis of test accuracy studies. bioRkiv. https://doi.org/10.1101/2022.12.05.519131. 
  4. Baragilly, M., Nieves, D., Williamson, D. J., Peters, R. and Owen, D. (2022). Measuring the similarity of SMLM-derived point-clouds. bioRkiv. https://doi.org/10.1101/2022.09.12.507560.
  5. Gabr, H., Baragilly, M. and Willis, B. H. (2022). Measuring and exploring mental health determinants: a closer look at co-residents’ effect using a multilevel structural equations model. BMC Medical Research Methodology. https://doi.org/10.1186/s12874-022-01711-9. 
  6. Baragilly, M. and Willis, B. H. (2022). On estimating a constrained bivariate random effects model for meta-analysis of test accuracy studies. Statistical Methods in Medical Research. https://doi.org/10.1177/09622802211065157 . 
  7. Baragilly, M., Gabr, H. and Willis, B. H. (2021).  Clustering functional data using the forward search based on functional spatial ranks with medical applications. Statistical Methods in Medical Research. https://doi.org/10.1177/09622802211002865.
  8. Willis, B. H., Coomar, D. and Baragilly, M. (2020). Clinical scores in primary care. British Journal of General Practice. 28; 70. https://doi.org/10.3399/bjgp20X709985. PMID: 32467198.
  9. Willis, B. H., Coomar, D. and Baragilly, M. (2019). Comparison of Centor and McIsaac scores: a meta-analysis over multiple thresholds. British Journal of General Practice. https://doi.org/10.3399/bjgp20X708833.
  10. Willis, B. H., Baragilly, M. and Coomar, D. (2019). Maximum likelihood estimation based on Newton -Raphson iteration for the bivariate random effects model in test accuracy meta-analysis. Statistical Methods in Medical Research.  https://doi.org/10.1177/0962280219853602
  11. Willis, B. H., Coomar, D. and Baragilly, M. (2019). Tailored meta-analysis: an investigation of the correlation between the test positive rate and prevalence. Journal of Clinical Epidemiology. 106, pp. 1-9.
  12. Willis B, Baragilly M, Coomar D. Estimating the parameters to a bivariate random-effects model in test accuracy meta-analysis using standard approaches. Abstracts of the 25th Cochrane Colloquium, Edinburgh, UK. Cochrane Database of Systematic Reviews 2018;(9 Suppl 1). https://doi.org/10.1002/14651858.CD201801.
  13. Willis, B. H., Coomar, D. and Baragilly, M. (2018). The effects of correlation between the test positive rate and prevalence on tailored meta-analysis. In: Diagnostic and Prognostic Research. 2 (Supplement 1), 12, O37.
  14. Baragilly, M. and Chakraborty, B. (2016). Determining the number of clusters using multivariate ranks. In: Agostinelli, C., Basu, A., Filzmoser, P., Mukherjee, D. (Eds.), Recent Advances in Robust Statistics: Theory and Applications. Springer, Chapter 2, pp. 17 - 33.
  15. Baragilly, M. (2010). The exponential distribution statistical models and their applications in demography. Journal of Business Studies (J.B.S), N.(2), Page 201-210.
  16. Baragilly, M., Hassan, I. & Kamel, N. (2008). On maximum product of spacings (MPS) estimation for the right truncated exponential distribution. In: proceedings of the 22nd Annual International Conference in Topology and its Applications, Helwan University, pp. 116-125.

View all publications in research portal