Tom Kelsey

Prof Tom Kelsey is a Professor in the School of Computer Science at the University of St Andrews. His research focuses on data-driven computational methods for hypothesis generation and model development. He supervises four PhD students and has published extensively across AI applications in healthcare, oncology, and reproductive medicine. His work includes developing machine learning tools for clinical decision support, predictive modeling of cancer survivor outcomes, and optimizing assisted reproductive technologies. Notable contributions include studies on follicle analysis in IVF, Hodgkin lymphoma treatment protocols, and AI-driven human activity recognition systems.

Education and Affiliations: Prof Kelsey’s academic background includes expertise in computer science and biomedical applications. He is affiliated with interdisciplinary teams addressing global health challenges, particularly in low-resource settings. His research integrates computational techniques with clinical data to improve diagnostic accuracy and patient outcomes.

Research Interests: His work spans artificial intelligence, machine learning, oncology, fertility preservation, and healthcare technology. Specific areas include predictive models for ovarian function, AI in surgical decision-making, and smart healthcare systems for elderly monitoring. Collaborations involve institutions globally, focusing on translating computational innovations into clinical practice.

Grants and Funding: While specific grants are not detailed here, his publications indicate sustained engagement with health-focused research programs. His work often addresses gaps in resource-limited settings, such as affordable blood test-based interim analysis for pediatric cancers.

Labs/Teams: Active within the School of Computer Science’s interdisciplinary research groups, Prof Kelsey collaborates with medical professionals to advance AI applications in healthcare. His team develops tools for clinical validation, predictive analytics, and personalized medicine solutions.