Watson, D. S., Krutzinna, J., Bruce, I. N., Griffiths, C. E.M., McInnes, I. B. , Barnes, M. R. and Floridi, L. (2019) Clinical applications of machine learning algorithms: beyond the black box. British Medical Journal, 364, l886. (doi: 10.1136/bmj.l886) (PMID:30862612)
|
Text
182884.pdf - Accepted Version 212kB |
Abstract
To maximise the clinical benefits of machine learning algorithms, we need to rethink our approach to explanation, argue David Watson and colleagues.
Item Type: | Articles |
---|---|
Status: | Published |
Refereed: | Yes |
Glasgow Author(s) Enlighten ID: | McInnes, Professor Iain |
Authors: | Watson, D. S., Krutzinna, J., Bruce, I. N., Griffiths, C. E.M., McInnes, I. B., Barnes, M. R., and Floridi, L. |
College/School: | College of Medical Veterinary and Life Sciences > School of Infection & Immunity |
Research Centre: | College of Medical Veterinary and Life Sciences > School of Infection & Immunity > Centre for Immunobiology |
Journal Name: | British Medical Journal |
Publisher: | BMJ Publishing Group |
ISSN: | 1759-2151 |
ISSN (Online): | 1756-1833 |
Copyright Holders: | Copyright © 2019 The Authors |
First Published: | First published in British Medical Journal 364:l886 |
Publisher Policy: | Reproduced in accordance with the copyright policy of the publisher |
University Staff: Request a correction | Enlighten Editors: Update this record