Machine learning to predict early recurrence after oesophageal cancer surgery

Autor: S A Rahman, R C Walker, M A Lloyd, B L Grace, G I van Boxel, B F Kingma, J P Ruurda, R van Hillegersberg, S Harris, S Parsons, S Mercer, E A Griffiths, J R O'Neill, R Turkington, R C Fitzgerald, T J Underwood, Ayesha Noorani, Rachael Fels Elliott, Paul A W Edwards, Nicola Grehan, Barbara Nutzinger, Jason Crawte, Hamza Chettouh, Gianmarco Contino, Xiaodun Li, Eleanor Gregson, Sebastian Zeki, Rachel de la Rue, Shalini Malhotra, Simon Tavaré, Andy G Lynch, Mike L Smith, Jim Davies, Charles Crichton, Nick Carroll, Peter Safranek, Andrew Hindmarsh, Vijayendran Sujendran, Stephen J Hayes, Yeng Ang, Shaun R Preston, Sarah Oakes, Izhar Bagwan, Vicki Save, Richard J E Skipworth, Ted R Hupp, J Robert O'Neill, Olga Tucker, Andrew Beggs, Philippe Taniere, Sonia Puig, Timothy J Underwood, Fergus Noble, James P Byrne, Jamie J Kelly, Jack Owsley, Hugh Barr, Neil Shepherd, Oliver Old, Jesper Lagergren, James Gossage, Andrew Davies Fuju Chang, Janine Zylstra, Vicky Goh, Francesca D Ciccarelli, Grant Sanders, Richard Berrisford, Catherine Harden, David Bunting, Mike Lewis, Ed Cheong, Bhaskar Kumar, Simon L Parsons, Irshad Soomro, Philip Kaye, John Saunders, Laurence Lovat, Rehan Haidry, Victor Eneh, Laszlo Igali, Michael Scott, Shamila Sothi, Sari Suortamo, Suzy Lishman, George B Hanna, Christopher J Peters, Anna Grabowska

Publikováno v: on behalf of the OCCAMS Consortium, Rahman, S A, Walker, R C, Lloyd, M A, Grace, B L, van Boxel, G I, Kingma, B F, Ruurda, J P, van Hillegersberg, R, Harris, S, Parsons, S, Mercer, S, Griffiths, E A, O'Neill, J R, Turkington, R, Fitzgerald, R C & Underwood, T J 2020, ' Machine learning to predict early recurrence after oesophageal cancer surgery ', British Journal of Surgery, vol. 107, no. 8, pp. 1042-1052 . https://doi.org/10.1002/bjs.11461
The British Journal of Surgery

Background Early cancer recurrence after oesophagectomy is a common problem, with an incidence of 20–30 per cent despite the widespread use of neoadjuvant treatment. Quantification of this risk is difficult and existing models perform poorly. This

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