Summary
Hadi is an NIHR Academic Clinical Fellow in Trauma and Orthopaedics at the MSk Lab and a Senior Teaching Fellow in Patient Safety and Health Policy at the Institute of Global Health Innovation of Imperial College London. He is a Senior Fellow of the Higher Education Academy and a Visiting Senior Fellow at the London School of Economics Data Science Institute. Hadi is the recipient of the prestigious Imperial College President's PhD Scholarship award and he undertakes his doctoral studies at the MSk Lab and the Biomechanics Research Group with Professor Justin Cobb and Professor Jonathan Jeffers. He is also an alumnus of Harvard Medical School's Safety, Quality, Informatics, and Leadership programme.
Background
Hadi started his medical studies in Aleppo, Syria and completed his medical degree at the University of Debrecen graduating summa cum laude (1st Class Honours). During his medical studies, he undertook medical electives in Canada, Austria, Germany, Ireland, and the UK. He completed his MSc in Sports and Exercise Medicine at the University of Nottingham with Distinction. With a devotion to medical education, Hadi completed a Master's in Education at the Centre for Medical Education of the University of Dundee, parallel to his clinical training and studies.
Hadi has been awarded several awards from various bodies, including:
- AI in Orthopaedics Poster Presentation Prize, ORUK
- Global Talent in Digital Technology Endorsement for Tier 1 visa, Tech Nation
- Outstanding Personal Tutoring Award (nominated), Imperial College Union
- Dubai Harvard Foundation for Medical Research Scholarship, Harvard Medical School
- Faculty of Medicine Dean's Internship Award, Imperial College London
- President's Prize - Orthopaedics Section, Royal Society of Medicine
- President's PhD Scholarship, Imperial College London
- Talent UD Scholarship and Diploma, University of Debrecen
- Four Excellent Student Scholarship Awards, University of Debrecen
- Silver Student Leader Award, University of Nottingham
- Finalist for the Rhodes Scholarship, Rhodes House, University of Oxford
Research Interests
Hadi's research interests are in the optimisation of patient safety through the use of big data, Artificial Intelligence technologies and medical education research.
Through a collaboration with the London School of Economics and the Swedish Hip Joint Registry, Hadi currently leads an international collaborative project focusing on predicting adverse outcomes to enhance safety and quality following joint replacement surgeries.
At Harvard-MIT Division of Health Science and Technology, Hadi is working with researchers in Boston, New Zealand and at IBM Research to develop Natural Language Processing (NLP) and Machine Learning (ML) algorithms that automate the diagnosis and prevent harm following treatment injuries.
Hadi leads medical education research focusing on building capacities for effective virtual mentorship and supervision across different settings (UG and PG) and settings (developed countries and LMICs). He is passionate to understand the dilemmas of Graduate-Entry Medicine (GEM) to harness skills for effective learner-tutor partnership.
Teaching summary
- Senior Teaching Fellow in Patient Safety and Health Policy - Institute of Global Health Innovation - Imperial College London
Aug 2022 - Present - Teaching Fellow in Patient Safety and Health Policy - Institute of Global Health Innovation - Imperial College London
Nov 2020 - July 2022 - Research Supervisor for BSc in Surgical Design, Technology and Innovation - Imperial College London
Jan 2020 - June 2022 - Tutor - Problem-Based Learning for undergraduate medical students Year 1 - Imperial College London
Oct 2018 - May 2022 - Tutor - Gross Anatomy for physiotherapy students - University of Debrecen
Sep 2016 - Feb 2017
Languages
Arabic (native), English (fluent), Hungarian (professional), French (intermediate)
Publications
Alagha, M.A., Logishetty, K., O’Hanlon, C., Liddle, A., Cobb, J. (2023). Three-dimensional preoperative planning software for hip resurfacing arthroplasty. Bioengineering.
Zhao, Y. Alagha, M.A., Cobb, J.P., Jones, G. (2023). Comparing Machine Learning to Statistical Methods in Predicting Health-Related Quality of Life Improvement in Osteoarthritis Patients. ORUK Conference. (Supervisor)
Nair, A., Alagha, M.A., Cobb, J.P., Jones, G. (2023). A Machine Learning Approach To Evaluate The Importance Of Imaging In Predicting WOMAC Scores For Knee Osteoarthritis. ORUK Conference. (Supervisor)
Crespo, R.F., Neves, A.L., Alagha, M.A., Leis, M., Flott, K., Bray, O., Fontana, G., Peck, J., Aldred, V., Darzi, A. (2022). Preprint here
Mahmoud K., Alagha, M.A., Nowinka, Z., Jones, G. (2022). Predicting total knee replacement at 2 and 5 years in osteoarthritis patients using machine learning. BMJ Health & Care Informatics.
Nowinka, Z., Alagha, M.A., Mahmoud K., Jones, G. (2022). Predicting Depression In Patients With Knee Osteoarthritis Using Machine Learning Models. JMIR Formative Research.
Jordan, C., Thillainathan, S., Celi, L.A., Jones, L., Alagha, M.A. (2021). The use of a formative pedagogy lens to enhance and maintain supervisory relationships: Critical Review and Appreciative Inquiry. JMIR Medical Education. [In-press].
Alagha, M.A., Jones, L. (2021). Listening to student voice – Understanding student and faculty experience at two UK graduate entry programmes. BMC Medical Education. doi: 10.1186/s12909-021-02634-7
Alagha, M.A., Jaulin, F, Yeung, W., Celi, L.A., Cosgriff, C.V. and Myers, L. (2020). Patient Harm During COVID-19 Pandemic Using a Human Factors Lens to Promote Patient and Workforce Safety. Journal of Patient Safety. doi:10.1097/PTS.0000000000000798.
Alagha, M.A., Vago, J., Katona, E., Takacs, R. Van der Veen, D., Zakany, R. and Matta, C. (2020). A synchronised circadian clock enhances early chondrogenesis. Cartilage. doi:10.1177/1947603520903425.
Alagha, M.A., Alagha, M.A., Dunstan, E., Sperwer, O., Timmins, K. and Boszczyk, B.M. (2017). Development of a new assessment tool for cervical myelopathy using hand-tracking sensor: Part 1: validity and reliability Eur Spine J. doi:10.1007/s00586-017-4948-3.
Alagha, M.A., Alagha, M.A., Dunstan, E., Sperwer, O., Timmins, K. and Boszczyk, B.M. (2017). Development of a new assessment tool for cervical myelopathy using hand-tracking sensor: Part 2: normative values. Eur Spine J. doi:10.1007/s00586-017-4949-2
Book Chapters:
Alagha, M.A., Young-Gough, A., Lyndon, M., Walker, X., Cobb, J., Celi, L.A, Waters, D.L. Artificial Intelligence in Medicine and Patient Safety In: Artificial Intelligence in Medicine. Springer Nature. doi:10.1007/978-3-030-58080-3_272-1
Publications
Journals
Alagha MA, Logishetty K, O’Hanlon C, et al., 2023, Three-dimensional preoperative planning software for hip resurfacing arthroplasty, Bioengineering, Vol:10, ISSN:2306-5354, Pages:1-10
Mahmoud K, Alagha MA, Nowinka Z, et al., 2023, Predicting total knee replacement at 2 and 5 years in osteoarthritis patients using machine learning, Bmj Surgery, Interventions, & Health Technologies, Vol:5, ISSN:2631-4940, Pages:1-9