Article info
PDFClinical ethics
Machine learning in medicine: should the pursuit of enhanced interpretability be abandoned?
- Correspondence to Dr Chang Ho Yoon, Big Data Institute, Oxford University, Oxford OX3 9DU, UK; changho.yoon{at}gmail.com
Citation
Machine learning in medicine: should the pursuit of enhanced interpretability be abandoned?
Publication history
- Received November 25, 2020
- Revised March 21, 2021
- Accepted April 8, 2021
- First published May 18, 2021.
Request permissions
If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.
Copyright information
© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY. Published by BMJ. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.
Other content recommended for you
- What is machine learning?
- Consistency of variety of machine learning and statistical models in predicting clinical risks of individual patients: longitudinal cohort study using cardiovascular disease as exemplar
- Implementation of prognostic machine learning algorithms in paediatric chronic respiratory conditions: a scoping review
- Machine learning in cardiovascular medicine: are we there yet?
- Future of machine learning in paediatrics
- Predicting the 10-year risk of cataract surgery using machine learning techniques on questionnaire data: findings from the 45 and Up Study
- Machine learning algorithm can provide assistance for the diagnosis of non-ST-segment elevation myocardial infarction
- Evidence-based medicine and machine learning: a partnership with a common purpose
- Machine learning techniques for mortality prediction in emergency departments: a systematic review
- AI: simply reinforcing medicine’s worst biases?