caa a22 4500 477073069 CHVBK 20180405111431.0 cr unu---uuuuu 170330e19960601xx s 000 0 eng 10.1007/BF01413746 doi (NATIONALLICENCE)springer-10.1007/BF01413746 Neural network prediction of relapse in breast cancer patients [Elektronische Daten] [L. Tarassenko, R. Whitehouse, G. Gasparini, A. Harris] When a woman diagnosed as having breast cancer has a tumour removed, it is important to try and predict whether she is likely to relapse within, say, the next three years. In this paper, the performance of a neural network classifier trained on a number of prognostic indicators is shown to be better than that of the clinical experts working with the same information. To obtain meaningful statistics with the relatively small dataset available, the network is trained using a modified form of the leave-one-out method. A procedure is also introduced for investigating how much independentinformation each input parameter contributes. This shows that, in this type of retrospective study, the type of therapy given to the woman does not significantly affect the network's prediction of whether or not she will relapse within three years. Finally, since this problem, in common with many other medical problems, is plagued by a shortage of data, the final section of the paper reports on an investigation of whether or not multi-centre databases might be feasible. Springer-Verlag London Limited, 1996 Breast cancer nationallicence Prediction of outcome nationallicence Prognostic indicators nationallicence Neural network classifier nationallicence Multilayer perceptron nationallicence Leave-one-out method nationallicence Tarassenko L. Department of Engineering Science, University of Oxford, OX1 3PJ, Oxford, UK aut Whitehouse R. ICRF Clinical Oncology Unit, Churchill Hospital, Oxford, UK aut Gasparini G. Department of Oncology, St. Bortolo Regional Medical Centre, Vicenza, Italy aut Harris A. Department of Engineering Science, University of Oxford, OX1 3PJ, Oxford, UK aut Neural Computing & Applications Springer-Verlag 4/2(1996-06-01), 105-113 0941-0643 4:2<105 1996 4 521 https://doi.org/10.1007/BF01413746 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/BF01413746 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Tarassenko L. Department of Engineering Science, University of Oxford, OX1 3PJ, Oxford, UK aut NATIONALLICENCE 700 1- Whitehouse R. ICRF Clinical Oncology Unit, Churchill Hospital, Oxford, UK aut NATIONALLICENCE 700 1- Gasparini G. Department of Oncology, St. Bortolo Regional Medical Centre, Vicenza, Italy aut NATIONALLICENCE 700 1- Harris A. Department of Engineering Science, University of Oxford, OX1 3PJ, Oxford, UK aut NATIONALLICENCE 773 0- Neural Computing & Applications Springer-Verlag 4/2(1996-06-01), 105-113 0941-0643 4:2<105 1996 4 521 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer