Talks.cam will close on 1 July 2026, further information is available on the UIS Help Site
 

University of Cambridge > Talks.cam > Isaac Newton Institute Seminar Series > From Data to Decisions: Building the Digital Twin Framework for Personalised Kidney Cancer Surgery

From Data to Decisions: Building the Digital Twin Framework for Personalised Kidney Cancer Surgery

Add to your list(s) Download to your calendar using vCal

If you have a question about this talk, please contact nobody.

OOEW07 - Mathematical Foundations of Oncological Digital Twins

Digital Twins hold immense promise in oncology, particularly in their ability to personalize care through dynamic, patient-specific modelling.   This talk will highlight the development of the Digital Twin Assisted Surgery (DTAS) for kidney cancer surgeries, an initiative that bridges clinical practice, engineering, and data science. The project centres around integrating multimodal data such as radiological imaging, tumour complexity scores, surgical variables, and post-operative outcomes into a digital framework designed to inform surgical planning.   Beyond the technical architecture, our work is fundamentally shaped by clinical questions: How do we personalise surgery for anatomical and pathological variability? How do we ensure the kidney tumour has been fully resected?   The talk will reflect how clinicians and patients are involved at every stage of the model development, and how this work reflects a broader shift toward precision surgery. The ethical and practical considerations of embedding such tools in a high-stakes environment of cancer surgery will also be considered. Ultimately, this talk will present DTAS as the future of surgery, from theoretical principles to actual surgeries where the digital twin becomes a guide, enhancing rather than replacing surgical judgement.  

This talk is part of the Isaac Newton Institute Seminar Series series.

Tell a friend about this talk:

This talk is included in these lists:

Note that ex-directory lists are not shown.

 

© 2006-2025 Talks.cam, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity