Artificial Intelligence in Oncology

Artificial intelligence is transforming how we understand human disease. Our research develops machine learning methods and foundation models that integrate large-scale biomedical data to investigate disease mechanisms, predict health trajectories, and advance biomedical discovery.

We develop AI methods that learn from diverse data modalities, including electronic health records, pathology images, genomics, molecular profiling, spatial biology, and medical imaging. One of the lab’s flagship research programs is Delphi, a foundation model for human disease.

Our research combines methodological advances in artificial intelligence with applications to fundamental and clinically relevant questions. We develop multimodal learning approaches, large language models, and computational methods for integrating heterogeneous biomedical data. Current research includes disease prediction from longitudinal health records, AI-based digital and computational pathology, prediction of molecular tumour characteristics from routine histology, integration of pathology with genomic and imaging data, and AI-assisted approaches for biomedical research and diagnosis.

Working closely with clinical and experimental collaborators, we aim to use advances in artificial intelligence to generate new insights into cancer and other diseases and to contribute to more precise, data-driven biomedical research and diagnostics.

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