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Feasibility of Tree-based Machine Learning algorithms fed with surface electromyographic features to discriminate risk classes according to NIOSH
Research article (2022 IEEE International Symposium on Medical Measurements and Applications (MeMeA), 2022) · cited 12× · AI/ML
Feasibility of Tree-based Machine Learning algorithms fed with surface electromyographic features to discriminate risk classes according to NIOSH
Summary
Feasibility of Tree-based Machine Learning algorithms fed with surface electromyographic features to discriminate risk classes according to NIOSH is a scholarly article[1].
Key Facts
Feasibility of Tree-based Machine Learning algorithms fed with surface electromyographic features to discriminate risk classes according to NIOSH's instance of is recorded as scholarly article[2].
References
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APA4ort.xyz Knowledge Graph. (2026). Feasibility of Tree-based Machine Learning algorithms fed with surface electromyographic features to discriminate risk classes according to NIOSH. Retrieved May 24, 2026, from https://4ort.xyz/entity/feasibility-of-tree-based-machine-learning-algorithms-fed-with-surface-electromyographic-features-to-discriminate-risk-c
MLA“Feasibility of Tree-based Machine Learning algorithms fed with surface electromyographic features to discriminate risk classes according to NIOSH.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/feasibility-of-tree-based-machine-learning-algorithms-fed-with-surface-electromyographic-features-to-discriminate-risk-c.
BibTeX@misc{4ortxyz_feasibility-of-tree-based-machine-learning-algorithms-fed-with-surface-electromyographic-features-to-discriminate-risk-c_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Feasibility of Tree-based Machine Learning algorithms fed with surface electromyographic features to discriminate risk classes according to NIOSH}}, year = {2026}, url = {https://4ort.xyz/entity/feasibility-of-tree-based-machine-learning-algorithms-fed-with-surface-electromyographic-features-to-discriminate-risk-c}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Feasibility of Tree-based Machine Learning algorithms fed with surface electromyographic features to discriminate risk classes according to NIOSH — https://4ort.xyz/entity/feasibility-of-tree-based-machine-learning-algorithms-fed-with-surface-electromyographic-features-to-discriminate-risk-c (retrieved 2026-05-24)
