Mr Huw Strafford

Research Assistant

Biomedical Sciences

h.a.strafford@swansea.ac.uk

Fluent Welsh Speaker

Available For Postgraduate Supervision

Research Links

ResearchGate

ResearcherID

About

Huw Strafford is a Researcher and Data Scientist at Swansea University. Huw is a part of the Neurology Research Group. His main research is focused on Natural Language Processing (NLP) but is also experienced with data linkage, analysis and visualisation within the SAIL Databank.

Areas Of Expertise

Natural Language Processing
Routinely Collected Data
Health Data Science
Machine Learning

Publications

Research Highlights

Dobbie, S., Strafford, H., Pickrell, O., Fonferko-Shadrach, B., Akbari, A., Ellwood-Thompson, S., & Lacey, A. (2020). Markup: A Web-Based Clinical Annotation Tool with Enhanced Ontology Mapping. In International Journal of Population Data ScienceSwansea University.
https://doi.org/10.23889/ijpds.v5i5.1634, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa55875
Miah, L., Strafford, H., Fonferko-Shadrach, B., Hollinghurst, J., Sawhney, I., Hadjikoutis, S., Rees, M., Powell, R., Lacey, A., & Pickrell, O. (2021). Incidence, Prevalence, and Health Care Outcomes in Idiopathic Intracranial Hypertension. Neurology, 96(8), e1251-e1261.
https://doi.org/10.1212/wnl.0000000000011463, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa56133
Dobbie, S., Strafford, H., Pickrell, O., Fonferko-Shadrach, B., Jones, C., Akbari, A., Ellwood-Thompson, S., & Lacey, A. (2021). Markup: A Web-Based Annotation Tool Powered by Active Learning. Frontiers in Digital Health, 3
https://doi.org/10.3389/fdgth.2021.598916, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa57479
Ali, S., Strafford, H., Dobbs, T., Fonferko-Shadrach, B., Lacey, A., Pickrell, O., Hutchings, H., & Whitaker, I. (2022). Development and validation of an automated basal cell carcinoma histopathology information extraction system using natural language processing. Frontiers in Surgery, 9
https://doi.org/10.3389/fsurg.2022.870494, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa60444
Ali, S., Dobbs, T., Jovic, M., Strafford, H., Fonferko-Shadrach, B., Lacey, A., Williams, N., Pickrell, O., Hutchings, H., & Whitaker, I. (2023). Validating a novel natural language processing pathway for automated quality assurance in surgical oncology: incomplete excision rates of 34 955 basal cell carcinomas. British Journal of Surgery, 110(9), 1072-1075.
https://doi.org/10.1093/bjs/znad055, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63002
http://dx.doi.org/10.1093/bjs/znad055

All Research

Journal Articles

Strafford, H., Hollinghurst, J., Lacey, A., Akbari, A., Watkins, A., Paterson, J., Jennings, D., Lyons, R., Powell, R., Kerr, M., Chin, R., & Pickrell, O. (2024). Epilepsy and the risk of COVID-19-related hospitalization and death: A population study. Epilepsia, 65(5), 1383-1393.
https://doi.org/10.1111/epi.17910, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa65804
Strafford, H., Hollinghurst, J., Lacey, A., Akbari, A., Watkins, A., Paterson, J., Jennings, D., Lyons, R., Powell, R., Kerr, M., Chin, R., & Pickrell, O. (2024). Health care utilization and mortality for people with epilepsy during COVID‐19: A population study. Epilepsia, 65(5), 1394-1405.
https://doi.org/10.1111/epi.17920, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa65805
Ali, S., Dobbs, T., Tarafdar, A., Strafford, H., Fonferko-Shadrach, B., Lacey, A., Pickrell, O., Hutchings, H., & Whitaker, I. (2024). Natural language processing to automate a web-based model of care and modernize skin cancer multidisciplinary team meetings. British Journal of Surgery, 111(1)
https://doi.org/10.1093/bjs/znad347, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa65543
Ali, S., Dobbs, T., Jovic, M., Strafford, H., Lacey, A., Williams, N., Pickrell, O., Hutchings, H., & Whitaker, I. (2024). Revisiting basal cell carcinoma clinical margins: Leveraging natural language processing and multivariate analysis with updated Royal College of Pathologists histological reporting standards. Journal of Plastic, Reconstructive and Aesthetic Surgery, 88, 443-451.
https://doi.org/10.1016/j.bjps.2023.10.106, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64779
Fonferko-Shadrach, B., Lacey, A., Strafford, H., Jones, C., Baker, M., Powell, R., Akbari, A., Lyons, R., Ford, D., Ellwood-Thompson, S., Jones, K., Chung, S., Pickrell, O., & Rees, M. (2023). Genetic influences on epilepsy outcomes: a whole‐exome sequencing and healthcare records data linkage study. Epilepsia
https://doi.org/10.1111/epi.17766, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa64175
http://dx.doi.org/10.1111/epi.17766
Strafford, H., Lacey, A., Hollinghurst, J., Akbari, A., Watkins, A., Paterson, J., Jennings, D., Lyons, R., Powell, R., Kerr, M., Chin, R., & Pickrell, O. (2023). COVID-19 vaccination uptake in people with epilepsy in wales. Seizure, 108, 49-52.
https://doi.org/10.1016/j.seizure.2023.04.006, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63099
http://dx.doi.org/10.1016/j.seizure.2023.04.006
Ali, S., Dobbs, T., Jovic, M., Strafford, H., Fonferko-Shadrach, B., Lacey, A., Williams, N., Pickrell, O., Hutchings, H., & Whitaker, I. (2023). Validating a novel natural language processing pathway for automated quality assurance in surgical oncology: incomplete excision rates of 34 955 basal cell carcinomas. British Journal of Surgery, 110(9), 1072-1075.
https://doi.org/10.1093/bjs/znad055, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa63002
http://dx.doi.org/10.1093/bjs/znad055
Ali, S., Strafford, H., Dobbs, T., Fonferko-Shadrach, B., Lacey, A., Pickrell, O., Hutchings, H., & Whitaker, I. (2022). Development and validation of an automated basal cell carcinoma histopathology information extraction system using natural language processing. Frontiers in Surgery, 9
https://doi.org/10.3389/fsurg.2022.870494, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa60444
Dobbie, S., Strafford, H., Pickrell, O., Fonferko-Shadrach, B., Jones, C., Akbari, A., Ellwood-Thompson, S., & Lacey, A. (2021). Markup: A Web-Based Annotation Tool Powered by Active Learning. Frontiers in Digital Health, 3
https://doi.org/10.3389/fdgth.2021.598916, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa57479
Miah, L., Strafford, H., Fonferko-Shadrach, B., Hollinghurst, J., Sawhney, I., Hadjikoutis, S., Rees, M., Powell, R., Lacey, A., & Pickrell, O. (2021). Incidence, Prevalence, and Health Care Outcomes in Idiopathic Intracranial Hypertension. Neurology, 96(8), e1251-e1261.
https://doi.org/10.1212/wnl.0000000000011463, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa56133

Conference Contributions

Dobbie, S., Strafford, H., Pickrell, O., Fonferko-Shadrach, B., Akbari, A., Ellwood-Thompson, S., & Lacey, A. (2020). Markup: A Web-Based Clinical Annotation Tool with Enhanced Ontology Mapping. In International Journal of Population Data ScienceSwansea University.
https://doi.org/10.23889/ijpds.v5i5.1634, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa55875

Taught Modules

PMIM302 Introductory Analysis of Linked Health Data

This module introduces the topic of linked health data analysis at an introductory to intermediate level. It fills a gap in research training opportunities by combining the principles of health care epidemiology with hands-on practical exercises in the implementation of computing solutions. The module provides students with a theoretical grounding in the classroom on each topic, followed by a training session on the corresponding computing solutions. Students use anonymised linked health data files in the hands-on exercises. The computing component of the module assumes a basic familiarity with computing syntax used in programs such as SPSS and/or R and methods of basic statistical analysis.