Home ›
Entities
› academia
› Continuous blood pressure monitoring using photoplethysmography and electrocardiogram signals by random forest feature selection and GWO-GBRT prediction model
Continuous blood pressure monitoring using photoplethysmography and electrocardiogram signals by random forest feature selection and GWO-GBRT prediction model
Research article (Biomedical Signal Processing and Control, 2023) · cited 19× · AI/ML
Continuous blood pressure monitoring using photoplethysmography and electrocardiogram signals by random forest feature selection and GWO-GBRT prediction model
Summary
Continuous blood pressure monitoring using photoplethysmography and electrocardiogram signals by random forest feature selection and GWO-GBRT prediction model is a scholarly article[1].
Key Facts
Continuous blood pressure monitoring using photoplethysmography and electrocardiogram signals by random forest feature selection and GWO-GBRT prediction model'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). Continuous blood pressure monitoring using photoplethysmography and electrocardiogram signals by random forest feature selection and GWO-GBRT prediction model. Retrieved May 24, 2026, from https://4ort.xyz/entity/continuous-blood-pressure-monitoring-using-photoplethysmography-and-electrocardiogram-signals-by-random-forest-feature-s
MLA“Continuous blood pressure monitoring using photoplethysmography and electrocardiogram signals by random forest feature selection and GWO-GBRT prediction model.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/continuous-blood-pressure-monitoring-using-photoplethysmography-and-electrocardiogram-signals-by-random-forest-feature-s.
BibTeX@misc{4ortxyz_continuous-blood-pressure-monitoring-using-photoplethysmography-and-electrocardiogram-signals-by-random-forest-feature-s_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Continuous blood pressure monitoring using photoplethysmography and electrocardiogram signals by random forest feature selection and GWO-GBRT prediction model}}, year = {2026}, url = {https://4ort.xyz/entity/continuous-blood-pressure-monitoring-using-photoplethysmography-and-electrocardiogram-signals-by-random-forest-feature-s}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Continuous blood pressure monitoring using photoplethysmography and electrocardiogram signals by random forest feature selection and GWO-GBRT prediction model — https://4ort.xyz/entity/continuous-blood-pressure-monitoring-using-photoplethysmography-and-electrocardiogram-signals-by-random-forest-feature-s (retrieved 2026-05-24)