Data used for modelling oesophageal cancer MDT models

Data used for modelling oesophageal cancer MDT models in my thesis. The associated readMe file outlines the general data structure and variable headers.
While the Data is used as part of IRAS 233065 & IRAS 319540 studies, it was collected and consented for primarily under IRAS 233065 and a blank consent for this study is attached.

Data from within this final dataset has contributed to the following publications as of October 2025:

Thavanesan N, Naiseh M, Terol M, Rahman S, Hill S, Parfitt C, Walter’s Z, Ramchurn S, Markar S, Owen R, Maynard N, Azim T, Belkhatir Z, Perez E, McCord M, Underwood T, Vigneswaran G. The Oesophageal Cancer Multi-Disciplinary Tool: A co-designed, externally validated, machine learning clinical decision support system. Accepted for publication in Lancet: eClinicalMedicine(2025) 89, 103527. | Impact factor 10.0, CiteScore 17.0

Thavanesan N, Farahi A, Parfitt C, Belkhatir Z, Azim T, Perez Vallejos E, Walters Z, Ramchurn S, Underwood T, Vigneswaran G. Insights from Explainable AI in Oesophageal Cancer Team Decisions. Computers in Biology and Medicine (2024) 180: 108978 | Impact factor 6.3 CiteScore 13.0

Thavanesan N, Bodala I, Walters Z, Ramchurn S, Underwood TJ, Vigneswaran G. Machine learning to predict curative multidisciplinary team treatment decisions in oesophageal cancer. European Journal of Surgical Oncology. 2023 Nov;49(11):106986 PMID 37463827 | Impact factor: 2.9, CiteScore 6.1