Available Projects
Multimodal Artificial Intelligence Framework for Early and Explainable Diagnosis of Pancreatic Cancer
This project aims to develop an AI-powered multimodal framework integrating histopathological, radiological, and clinical data for early pancreatic cancer detection. Using deep learning and explainable AI, it will identify biomarkers, visualise diagnostic reasoning, and predict treatment responses, creating a transparent, data-driven tool to enhance diagnostic accuracy and support personalised oncology care.
Primary supervisor: Viji Ahanathapillai - Email: Viji.Ahanathapillai@warwick.ac.uk
Project detail:
Pancreatic cancer remains one of the most lethal malignancies due to late diagnosis and limited treatment options. Early detection of pancreatic cancer remains a major clinical challenge due to subtle morphological changes and limited sensitivity of current diagnostic techniques. This research proposes to develop an AI-powered multimodal data analysis and image processing framework that integrates histopathological (H&E) images, radiological data, clinical history and diagnostic reports to enable early, accurate, and interpretable diagnosis. The project will leverage advanced image processing, feature extraction, and deep learning architectures, including convolutional neural networks (CNNs) and vision transformers to identify discriminative patterns and textural biomarkers indicative of early-stage malignancy. The system will combine quantitative imaging features with patient-specific clinical parameters to enhance predictive accuracy. Explainable AI (XAI) techniques will be embedded to visualise decision pathways, providing clinicians with interpretable outputs and highlighting critical diagnostic regions within images. The framework will further explore predictive modelling for treatment response and disease progression, supporting precision oncology. The expected outcome is a robust, explainable, and clinically adaptable diagnostic tool that harnesses AI and image analytics to transform early pancreatic cancer detection, improve diagnostic confidence, and contribute to next-generation digital pathology and data-driven healthcare.
How to apply for admission: www.warwick.ac.uk/pgrengineering
How to apply for a scholarship: https://warwick.ac.uk/fac/sci/eng/postgraduate/funding/
The University of Warwick provides an inclusive working and learning environment, recognising and respecting every individual’s differences. We welcome applications from individuals who identify with any of the protected characteristics defined by the Equality Act 2010.