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Use of machine learning to identify patients at risk of sub-optimal adherence: study based on real-world data from 10,929 children using a connected auto-injector device
Research article (BMC Medical Informatics and Decision Making, 2022) · cited 16× · AI/ML
Use of machine learning to identify patients at risk of sub-optimal adherence: study based on real-world data from 10,929 children using a connected auto-injector device
Summary
Use of machine learning to identify patients at risk of sub-optimal adherence: study based on real-world data from 10,929 children using a connected auto-injector device is a scholarly article[1].
Key Facts
Use of machine learning to identify patients at risk of sub-optimal adherence: study based on real-world data from 10,929 children using a connected auto-injector device'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). Use of machine learning to identify patients at risk of sub-optimal adherence: study based on real-world data from 10,929 children using a connected auto-injector device. Retrieved May 24, 2026, from https://4ort.xyz/entity/use-of-machine-learning-to-identify-patients-at-risk-of-sub-optimal-adherence-study-based-on-real-world-data-from-10-929
MLA“Use of machine learning to identify patients at risk of sub-optimal adherence: study based on real-world data from 10,929 children using a connected auto-injector device.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/use-of-machine-learning-to-identify-patients-at-risk-of-sub-optimal-adherence-study-based-on-real-world-data-from-10-929.
BibTeX@misc{4ortxyz_use-of-machine-learning-to-identify-patients-at-risk-of-sub-optimal-adherence-study-based-on-real-world-data-from-10-929_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Use of machine learning to identify patients at risk of sub-optimal adherence: study based on real-world data from 10,929 children using a connected auto-injector device}}, year = {2026}, url = {https://4ort.xyz/entity/use-of-machine-learning-to-identify-patients-at-risk-of-sub-optimal-adherence-study-based-on-real-world-data-from-10-929}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Use of machine learning to identify patients at risk of sub-optimal adherence: study based on real-world data from 10,929 children using a connected auto-injector device — https://4ort.xyz/entity/use-of-machine-learning-to-identify-patients-at-risk-of-sub-optimal-adherence-study-based-on-real-world-data-from-10-929 (retrieved 2026-05-24)
