Computational Medicine
Computational Medicine develops and applies computational and AI methods to biomedical signals and neurological data, with the goal of improving diagnosis, treatment, and patient outcomes in neurology, cardiology, and circadian health.
Research group focus
Computational Medicine is an interdisciplinary research group based in the School of Computing at Newcastle University. We develop and apply computational, AI, and data science methods to complex biomedical data, working closely with clinicians and healthcare partners to translate our findings into real-world impact. Our research spans four main areas:
- computational neurology and epilepsy: Analysing brain structure, function, and connectivity using MRI, EEG, and intracranial recordings to understand and predict outcomes in epilepsy surgery, and to characterise how seizures affect the brain over time.
- computational neuroradiology: Applying advanced image analysis and machine learning to structural and diffusion MRI data to characterise brain abnormalities, map vascular architecture, and quantify white matter changes. This includes the study of brain morphology and the development of multivariate and normative models to capture how neurological conditions affect brain structure across individuals and over time.
- cardiac monitoring & AI: Developing explainable AI and novel visualisation methods for ECG interpretation, with a focus on detecting drug-induced cardiac risk and improving human-machine interfaces in clinical settings.
- chronobiology & circadian health: Investigating biological rhythms and their role in neurological and psychiatric conditions using wearable devices, continuous physiological monitoring, and machine learning.
Across all areas, we combine large multimodal datasets with rigorous computational methods to build tools that are both scientifically principled and clinically useful.
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Research impact
Computational Medicine's research has direct impact on clinical practice and patient care. Our work on epilepsy surgery prediction informs treatment decisions for patients with drug-resistant epilepsy, and our open tools and datasets — including the IDEAS database and BrainMoNoCle — are used by researchers internationally. In cardiac monitoring, our novel ECG visualisation methods have been recognised by the MIT Innovators Under 35 Award and the IET Healthcare Technology Awards. Our research is embedded in a wider network of clinical and scientific partnerships.
We collaborate closely with neurology and neurosurgery teams across the UK, and contribute to large international consortia. Our chronobiology work is developing new approaches to monitoring circadian health in real-world settings, with applications in mood disorders, epilepsy, and general wellbeing. The group sits at the intersection of several interdisciplinary specialities — including neuroimaging, signal processing, explainable AI, normative modelling, and human-computer interaction — and maintains active links with Newcastle's clinical neurosciences, the Newcastle Biomedical Research Centre, and the Centre for Transformative Neuroscience.
Key collaborators
Computational Medicine maintains active collaborations with clinical, academic, and industry partners across the UK and internationally. Our collaborative work spans epilepsy surgery, cardiac monitoring, chronobiology, and normative modelling, and includes both research partnerships and patient-facing clinical studies.
- University College London (UCL)
- Chalfont Centre for Epilepsy
- ENIGMA Consortium
- The Christie NHS Foundation Trust
- Cancer Research UK
- Newcastle upon Tyne Hospitals NHS Foundation Trust