Home ›
Entities
› academia
› Kernel machine learning methods to handle missing responses with complex predictors. Application in modelling five-year glucose changes using distributional representations
Kernel machine learning methods to handle missing responses with complex predictors. Application in modelling five-year glucose changes using distributional representations
Research article (Computer Methods and Programs in Biomedicine, 2022) · cited 17× · AI/ML
Kernel machine learning methods to handle missing responses with complex predictors. Application in modelling five-year glucose changes using distributional representations
Summary
Kernel machine learning methods to handle missing responses with complex predictors. Application in modelling five-year glucose changes using distributional representations is a scholarly article[1].
Key Facts
Kernel machine learning methods to handle missing responses with complex predictors. Application in modelling five-year glucose changes using distributional representations's instance of is recorded as scholarly article[2].
References
Programmatic citations — every numbered marker resolves to a verifiable graph row below.
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). Kernel machine learning methods to handle missing responses with complex predictors. Application in modelling five-year glucose changes using distributional representations. Retrieved May 24, 2026, from https://4ort.xyz/entity/kernel-machine-learning-methods-to-handle-missing-responses-with-complex-predictors-application-in-modelling-five-year-g
MLA“Kernel machine learning methods to handle missing responses with complex predictors. Application in modelling five-year glucose changes using distributional representations.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/kernel-machine-learning-methods-to-handle-missing-responses-with-complex-predictors-application-in-modelling-five-year-g.
BibTeX@misc{4ortxyz_kernel-machine-learning-methods-to-handle-missing-responses-with-complex-predictors-application-in-modelling-five-year-g_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Kernel machine learning methods to handle missing responses with complex predictors. Application in modelling five-year glucose changes using distributional representations}}, year = {2026}, url = {https://4ort.xyz/entity/kernel-machine-learning-methods-to-handle-missing-responses-with-complex-predictors-application-in-modelling-five-year-g}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Kernel machine learning methods to handle missing responses with complex predictors. Application in modelling five-year glucose changes using distributional representations — https://4ort.xyz/entity/kernel-machine-learning-methods-to-handle-missing-responses-with-complex-predictors-application-in-modelling-five-year-g (retrieved 2026-05-24)
