Adaptive treatment and robust control
- Submitting institution
-
The University of Lancaster
- Unit of assessment
- 12 - Engineering
- Output identifier
- 302073827
- Type
- D - Journal article
- DOI
-
10.1111/biom.13268
- Title of journal
- Biometrics
- Article number
- -
- First page
- 0
- Volume
- 0
- Issue
- -
- ISSN
- 0006-341X
- Open access status
- Compliant
- Month of publication
- April
- Year of publication
- 2020
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- Yes
- Number of additional authors
-
4
- Research group(s)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Key output from interdisciplinary £547k EPSRC-project (EP/M015637/1) that addresses uncertainty in personalised medicine, through the integration of techniques that have been developed in previously distinct fields, namely engineering, medical statistics and analysis. As a “bridging paper” (Reviewer 1), this article links, for the first time, the statistical regret paradigm to the state-space. Engineers can now exploit rigorous observational data modelling tools, whilst “control theory ideas [are] brought to applications in biostatistics” (ditto). As a result, medical treatment decisions that explicitly account for uncertainty can be developed. The warfarin example within illustrates impact scope, with 2+ million Europeans taking similar medicines.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
