Unintended consequences of machine learning in medicine?

F1000Res. 2017 Sep 19:6:1707. doi: 10.12688/f1000research.12693.1. eCollection 2017.

Abstract

Machine learning (ML) has the potential to significantly aid medical practice. However, a recent article highlighted some negative consequences that may arise from using ML decision support in medicine. We argue here that whilst the concerns raised by the authors may be appropriate, they are not specific to ML, and thus the article may lead to an adverse perception about this technique in particular. Whilst ML is not without its limitations like any methodology, a balanced view is needed in order to not hamper its use in potentially enabling better patient care.

Keywords: artificial intelligence; healthcare; machine learning; medicine.

Grants and funding

The author(s) declared that no grants were involved in supporting this work.