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REinforcement learning to improve non-adherence for diabetes treatments by Optimising Response and Customising Engagement (REINFORCE): study protocol of a pragmatic randomised trial
Research article (BMJ Open, 2021) · cited 20× · AI/ML
REinforcement learning to improve non-adherence for diabetes treatments by Optimising Response and Customising Engagement (REINFORCE): study protocol of a pragmatic randomised trial
Summary
REinforcement learning to improve non-adherence for diabetes treatments by Optimising Response and Customising Engagement (REINFORCE): study protocol of a pragmatic randomised trial is a scholarly article[1].
Key Facts
REinforcement learning to improve non-adherence for diabetes treatments by Optimising Response and Customising Engagement (REINFORCE): study protocol of a pragmatic randomised trial's instance of is recorded as scholarly article[2].
References
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Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). REinforcement learning to improve non-adherence for diabetes treatments by Optimising Response and Customising Engagement (REINFORCE): study protocol of a pragmatic randomised trial. Retrieved May 24, 2026, from https://4ort.xyz/entity/reinforcement-learning-to-improve-non-adherence-for-diabetes-treatments-by-optimising-response-and-customising-engagemen
MLA“REinforcement learning to improve non-adherence for diabetes treatments by Optimising Response and Customising Engagement (REINFORCE): study protocol of a pragmatic randomised trial.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/reinforcement-learning-to-improve-non-adherence-for-diabetes-treatments-by-optimising-response-and-customising-engagemen.
BibTeX@misc{4ortxyz_reinforcement-learning-to-improve-non-adherence-for-diabetes-treatments-by-optimising-response-and-customising-engagemen_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{REinforcement learning to improve non-adherence for diabetes treatments by Optimising Response and Customising Engagement (REINFORCE): study protocol of a pragmatic randomised trial}}, year = {2026}, url = {https://4ort.xyz/entity/reinforcement-learning-to-improve-non-adherence-for-diabetes-treatments-by-optimising-response-and-customising-engagemen}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): REinforcement learning to improve non-adherence for diabetes treatments by Optimising Response and Customising Engagement (REINFORCE): study protocol of a pragmatic randomised trial — https://4ort.xyz/entity/reinforcement-learning-to-improve-non-adherence-for-diabetes-treatments-by-optimising-response-and-customising-engagemen (retrieved 2026-05-24)
