OnRAMP for Regulating AI in Medical Products
- URL: http://arxiv.org/abs/2010.07038v6
- Date: Mon, 26 Jul 2021 11:51:05 GMT
- Title: OnRAMP for Regulating AI in Medical Products
- Authors: David Higgins
- Abstract summary: This Perspective proposes best practice guidelines for development compatible with the production of a regulatory package.
These guidelines will allow all parties to communicate more clearly in the development of a common Good Machine Learning Practice.
- Score: 0.0
- License: http://creativecommons.org/licenses/by-nc-sa/4.0/
- Abstract: Medical Artificial Intelligence (AI) involves the application of machine
learning algorithms to biomedical datasets in order to improve medical
practices. Products incorporating medical AI require certification before
deployment in most jurisdictions. To date, clear pathways for regulating
medical AI are still under development. Below the level of formal pathways lies
the actual practice of developing a medical AI solution. This Perspective
proposes best practice guidelines for development compatible with the
production of a regulatory package which, regardless of the formal regulatory
path, will form a core component of a certification process. The approach is
predicated on a statistical risk perspective, typical of medical device
regulators, and a deep understanding of machine learning methodologies. These
guidelines will allow all parties to communicate more clearly in the
development of a common Good Machine Learning Practice (GMLP), and thus lead to
the enhanced development of both medical AI products and regulations.
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