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1 Ergebnisse
1
Feasibility of Tree-based Machine Learning algorithms fed w..:
, In:
2022 IEEE International Symposium on Medical Measurements and Applications (MeMeA)
,
Donisi, Leandro
;
Capodaglio, Edda
;
Pagano, Gaetano
... - p. 1-6 , 2022
Link:
https://doi.org/10.1109/MeMeA54994.2022.9856521
RT T1 <cTitle>2022 IEEE International Symposium on Medical Measurements and Applications (MeMeA)</cTitle>: T1 <Title>Feasibility of Tree-based Machine Learning algorithms fed with surface electromyographic features to discriminate risk classes according to NIOSH</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-9856521&Exemplar=1&LAN=DE A1 Donisi, Leandro A1 Capodaglio, Edda A1 Pagano, Gaetano A1 Amitrano, Federica A1 Cesarelli, Mario A1 Panigazzi, Monica A1 D'Addio, Giovanni YR 2022 K1 Biomechanics K1 Musculoskeletal system K1 Machine learning algorithms K1 Occupational safety K1 Sociology K1 Feature extraction K1 Electromyography K1 Biomechanical risk assessment K1 bicep muscle K1 ergonomics K1 lifting K1 machine learning K1 Revised NIOSH lifting equation K1 work-related musculoskeletal disorders SP 1 OP 6 LK http://dx.doi.org/https://doi.org/10.1109/MeMeA54994.2022.9856521 DO https://doi.org/10.1109/MeMeA54994.2022.9856521 SF ELIB - SuUB Bremen
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