YSPR Design Research Workshop. Today,
we introduce Clodagh McDermott.
Dr Clodagh McDermott graduated top of her class from the University of Galway in 2016. She holds a Masters degree in Clinical Research, and was appointed to the Higher Specialist Training Scheme in Geriatric Medicine in 2021. As an ICAT Fellow, she commenced her PhD in 2023, which focuses on the integration of multi-modal diagnostics and machine learning techniques to improve early stroke diagnosis.
X. @Clodagh_Mcd
How did you get involved in stroke research?
My interest in stroke research began before I entered medical school. At 16 years of age, I became a carer for someone who had experienced a stroke. This gave me a firsthand understanding of the profound impact that a stroke can have on both patients, and their families. This experience motivated my academic focus on advancing early stroke diagnosis to facilitate timely interventions, to reduce morbidity, and to improve overall clinical outcomes.
What have been the most difficult challenges regarding your research career so far?
One of the most challenging aspects of my research career has been acquiring a new technical skillset in machine learning and artificial intelligence, which lay well outside the scope of my traditional clinical training. This has required dedication, a lot of long hours, open-mindedness, recognising my own limits, and a willingness to ask for help. Fundamentally, balancing research with the clinical demands of higher specialist training has required strong time management and sustained focus.
Why did you choose this topic and how do you think this may have an impact on future stroke care?
I chose this topic because I believe this work has the potential to reduce the impact of stroke on patients and families. Stroke diagnostics have traditionally been siloed, with clinical tools, imaging modalities, and biomarkers studied in isolation. Combining these into a multi-modal approach is a novel and promising direction. The use of machine learning and artificial intelligence enables more sophisticated analysis of data sources, potentially transforming early stroke diagnosis. This approach could have significant impact in remote or under-resourced settings, such as isolated regions or low- and middle-income countries, where access to neuroimaging is limited. By improving diagnostic accuracy without the use of costly neuroimaging and enabling timely, evidence-based treatment, this work could help reduce disparities in stroke care globally.
What inspires you?
I’m inspired by the potential to make a meaningful difference in patients’ lives through research and clinical care. Seeing how timely diagnosis and intervention can change outcomes, motivates me to keep striving for better diagnostic tools and therapeutic approaches. I am committed to advancing global stroke care by reducing inequities in access and ensuring that timely, effective treatment is available to all, regardless of geography or resources.
I’m also inspired by mentors and colleagues who challenge conventional thinking and are committed to improving the health system through innovation and compassion.
What can your mentor expect from you?
My mentor can expect a hardworking and diligent researcher who approaches every question with persistence and curiosity. I am committed to exploring all possible avenues before drawing conclusions. I strive to be open-minded, receptive to feedback, and collaborative. I bring a genuine enthusiasm for learning and strive to contribute positively to the research environment.
What is the best piece of advice you have received in your professional life?
The best advice I have received is to avoid groupthink, think independently, and stay true to my own perspective. Innovation often comes from questioning assumptions and thinking outside the box. Being authentic, not just following the crowd, has helped me stay grounded and pursue unconventional avenues, such as integrating non-conventional imaging modalities, machine learning, and AI into stroke research, that I believe have real potential to drive meaningful change.
