AI for Integrative Health

Our theme is highly interdisciplinary and involves topics in computer science, biology and medicine. 

We are experts in various computational approaches to study the workings of the human organism in health disease and help develop treatments. Notably, we are experienced in working together with domain experts across domains to leverage innovative computational models and tools, including health data science, network theory, AI and machine learning.

The theme comprises fundamental research and applications, including diagnosis, prognosis and treatment. Our methods often leverage advanced processing techniques and utilize complex and large real-world data (e.g., omics, imaging or neural activity data).

Meet the team

Roman Bauer profile image

Dr Roman Bauer

Senior Lecturer

Sotiris Moschoyiannis profile image

Dr Sotiris Moschoyiannis

Reader in Complex Systems

Tom Thorne profile image

Dr Tom Thorne

Senior Lecturer; Programme Lead of MSc Data Science

Professor H Lilian Tang

Professor in Artificial Intelligence

Alaa Marshan profile image

Dr Alaa Marshan

Senior Lecturer in Intelligent Data Analysis

List of outstanding recent achievements strictly related to the strategic theme

Selected Papers

  • Cogno, N., Bauer, R. and Durante, M., “Mechanistic model of radiotherapy-induced lung fibrosis using coupled 3D agent-based and Monte Carlo simulations”. Communications Medicine (Nature), 4(1), p.16. 2024. https://doi.org/10.1038/s43856-024-00442-w
  • S. Moschoyiannis, E. Chatzaroulas, V. Šliogeris and Y. Wu, "Deep Reinforcement Learning for Stabilization of Large-Scale Probabilistic Boolean Networks",  IEEE Transactions on Control of Network Systems, vol. 10, no. 3, pp. 1412-1423, 2023.  10.1109/TCNS.2022.3232527.
  • Jennings, J.L., Peraza, L.R., Baker, M., Alter, K., Taylor, J.P. and Bauer, R. “Investigating the power of eyes open resting state EEG for assisting in dementia diagnosis”. Alzheimer's research & therapy, 14(1), p.109. 2022. https://doi.org/10.1186/s13195-022-01046-z
  • Al-Turk, L., Wawrzynski, J., Wang, S., Krause, P., Saleh, G.M., Alsawadi, H., Alshamrani, A.Z., Peto, T., Bastawrous, A., Li, J. and Tang, H.L. Automated feature-based grading and progression analysis of diabetic retinopathy. Eye (Nature), 36(3), pp.524-532. 2022. https://doi.org/10.1038/s41433-021-01415-2
  • Perryman, R., Renziehausen, A., Shaye, H., Kostagianni, A.D., Tsiailanis, A.D., Thorne, T., Chatziathanasiadou, M.V., Sivolapenko, G.B., El Mubarak, M.A., Han, G.W. and Zarzycka, B. Inhibition of the angiotensin II type 2 receptor AT2R is a novel therapeutic strategy for glioblastoma. Proceedings of the National Academy of Sciences, 119(32), p.e2116289119. 2022. 10.1073/pnas.2116289119
  • Mahmood, I., Arabnejad, H., Suleimenova, D., Sassoon, I., Marshan, A., Serrano-Rico, A., Louvieris, P., Anagnostou, A., JE Taylor, S., Bell, D. and Groen, D. FACS: a geospatial agent-based simulator for analysing COVID-19 spread and public health measures on local regions. Journal of Simulation, 16(4), pp.355-373. 2022. 10.1080/17477778.2020.1800422
  • Marshan A, Almutairi AN, Ioannou A, Bell D, Monaghan A and Arzoky M. MedT5SQL: a transformers-based large language model for text-to-SQL conversion in the healthcare domain. Front. Big Data 7:1371680. 2024. 10.3389/fdata.2024.1371680
  • Topological Approximate Bayesian Computation for Parameter Inference of an Angiogenesis Model Thorne T, Kirk PDW, Harrington HA, Bioinformatics, Volume 38, Issue 9, Pages 2529–2535, 2022. https://doi.org/10.1093/bioinformatics/btac118

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School of Computer Science and Electronic Engineering
University of Surrey
Guildford
Surrey
GU2 7XH
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