University of Cambridge > Talks.cam > Foundation AI > Deep Learning Approaches for Label-Free Tumour Image Segmentation Spectroscopy in Cancer Diagnosis

  Browse A-Z

Log in

University Account External (via Google)

🔐 Log In

Information on

Subscribing to talksdetails Finding a talkdetails Adding a talkdetails Disseminating talksdetails Help and Documentationdetails

ℹ️ Information

Deep Learning Approaches for Label-Free Tumour Image Segmentation Spectroscopy in Cancer Diagnosis

Download to your calendar using vCal

If you have a question about this talk, please contact Pietro Lio .

In this talk, I will present results showing the performance of MSE , PCA-> LDA , PCA->XGBoost, XGBoost and novel Ensemble Scale-Invariant CNN models in the context of tissue classification for cancer diagnosis using Fourier Transform Infrared Spectroscopy biopsy images. I will then discuss the explainability of those models using LIME [1] to reveal wavenumber ranges of particular importance for this classification task, before extending the CRIME framework [2] using custom semi-supervised VAE models to identify clustered explanation patterns. Finally, I will show how these clustered explanation patterns can be used to produce a model-agnostic, fully explainable linear predictive model for classification purposes.

[1] Ribeiro, Marco Tulio, Sameer Singh, and Carlos Guestrin. ‘“Why Should I Trust You?”: Explaining the Predictions of Any Classifier’. arXiv, 9 August 2016. https://doi.org/10.48550/arXiv.1602.04938.

[2] Zaki, Jihan K., Jakub Tomasik, Jade A. McCune, Sabine Bahn, Pietro Liò, and Oren A. Scherman. ‘Explainable Deep Learning Framework for SERS Bio-Quantification’. arXiv, 12 November 2024. https://doi.org/10.48550/arXiv.2411.08082.

This talk is part of the Foundation AI series.

This talk is included in these lists:

Note that ex-directory lists are not shown.

Other lists

Social Anthropology Post-Doc Seminar Goldsmiths' 2 & https://zoom.us/j/96836714124 Type the title of a new list here

Other talks

Chemical strategies for biomolecule functionalisation, and biomaterial conjugation Title to be confirmed Group Work Peri-Operative Medicine, and Obstetrics and Gynaecology Welfare Reform and the Imperative of Cooperation Fairy Tales
 

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