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Adaptive Biomedical Treatment and Robust Control

Lookup NU author(s): Dr Quentin Clairon

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Abstract

© 2017 An adaptive treatment strategy is a set of rules for choosing effective medical treatments for individual patients. In the statistical literature, methods for optimal dynamic treatment (ODT) include Q-learning and A-learning methods, which are linked to machine learning in engineering and computer science. The research project behind this article aims to develop new methodology for both ODT and engineering control, through the integration of techniques and approaches that have been developed in both fields, with a particular focus on the problem of robustness. The methodological framework is based on a regret-regression approach from the statistical literature and non-minimal state-space methods from control. This article provides an introduction to some of these concepts and presents preliminary novel contributions based on the application of robust H∞ methods to ODT problems.

Publication metadata

Author(s): Clairon Q, Wilson ED, Henderson R, Taylor CJ

Publication type: Article

Publication status: Published

Journal: IFAC-PapersOnLine

Year: 2017

Volume: 50

Issue: 1

Pages: 12191-12196

Print publication date: 01/07/2017

Online publication date: 18/10/2017

Acceptance date: 01/01/1900

Publisher: Elsevier B.V.

URL: https://doi.org/10.1016/j.ifacol.2017.08.2274

DOI: 10.1016/j.ifacol.2017.08.2274

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