Analysing PET scans data for predicting response to chemotherapy in breast cancer patients

Gyftodimos, E., Moss, L. , Sleeman, D. and Welch, A. (2008) Analysing PET scans data for predicting response to chemotherapy in breast cancer patients. In: Ellis, R., Allen, T. and Petridis, M. (eds.) Applications and Innovations in Intelligent Systems XV: Proceedings of AI-2007, the Twenty-seventh SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence. Springer: London, pp. 59-72. ISBN 9781848000858 (doi: 10.1007/978-1-84800-086-5_5)

Abstract

We discuss the use of machine learning algorithms to predict which breast cancer patients are likely to respond to (neoadjunctive) chemotherapy. A group of 96 patients from the Aberdeen Royal Infirmary had the size of their tumours assessed by Positron Emission Tomography at various stages of their chemotherapy treatment. The aim is to predict at an early stage which patients have low response to the therapy, for which alternative treatment plans should be followed. A variety of machine learning algorithms were used with this data set. Results indicate that machine learning methods outperform previous statistical approaches on the same data set.

• Item Type: Book Sections
• Status: Published
• Glasgow Author(s) Enlighten ID: Moss, Dr Laura
• Authors: Gyftodimos, E., Moss, L., Sleeman, D., and Welch, A.
• College/School: College of Medical Veterinary and Life Sciences > School of Medicine, Dentistry & Nursing
• Publisher: Springer
• ISBN: 9781848000858