Published in bioRxiv, 2022
Recommended citation: Matt De Vries, Lucas Dent, Nathan Curry, Leo Rowe-Brown, Adam Tyson, Christopher Dunsby, and Chris Bakal. 3D single-cell shape analysis of cancer cells using geometric deep learning. 17 June 2022; bioRxiv 2022.06.17.496550; doi: https://doi.org/10.1101/2022.06.17.496550
Published in British Journal of Surgery, 2021
Recommended citation: Saqib Rahman, Joseph Early, Ben Sharpe, Megan Lloyd, Matt De Vries, Ben Grace, Sarvapali Ramchurn, and Timothy Underwood. P-OGC57 Predicting survival and response to therapy using diagnostic biopsies: A machine learning approach to facilitate treatment decisions for oesophageal adenocarcinoma. British Journal of Surgery, 108
Published in The Biochemist, 2021
Recommended citation: Matt De Vries, Chris Bakal; What do machines see? Utilizing artificial intelligence to explore cell biology. Biochem (Lond) 1 October 2021; 43 (5): 48–52. doi: https://doi.org/10.1042/bio_2021_168
Published in European Journal of Surgical Oncology, 2021
Recommended citation: Saqib Rahman, Joe Early, Matt De Vries, Megan Lloyd, Ben Grace, Gopal Ramchurn, and Timothy Underwood. Predicting response to neoadjuvant therapy using image capture from diagnostic biopsies of oesophageal adenocarcinoma. European Journal of Surgical Oncology, 47(1):e4, 2021 https://github.com/DeVriesMatt/DeVriesMatt.github.io/blob/master/files/2020-predicting-response.pdf