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Full-Text Articles in Medicine and Health Sciences
Vertical Federated Learning Using Autoencoders With Applications In Electrocardiograms, Wesley William Chorney
Vertical Federated Learning Using Autoencoders With Applications In Electrocardiograms, Wesley William Chorney
Theses and Dissertations
Federated learning is a framework in machine learning that allows for training a model while maintaining data privacy. Moreover, it allows clients with their own data to collaborate in order to build a stronger, shared model. Federated learning is of particular interest to healthcare data, since it is of the utmost importance to respect patient privacy while still building useful diagnostic tools. However, healthcare data can be complicated — data format might differ across providers, leading to unexpected inputs and incompatibility between different providers. For example, electrocardiograms might differ in sampling rate or number of leads used, meaning that a …
A Comparison Of Ground Reaction Forces And Muscle Activity Of The Tsunami Bar® Against A Rigid Barbell During Back Squat Phases, John Carver Middleton
A Comparison Of Ground Reaction Forces And Muscle Activity Of The Tsunami Bar® Against A Rigid Barbell During Back Squat Phases, John Carver Middleton
Theses and Dissertations
An Institutional Review Board (IRB)-approved study was conducted to investigate the effects of the Tsunami Bar® (TB), a flexible barbell, on ground reaction force (GRF) production and muscle activity in the quadricep, hamstring, and gluteal muscle groups during phases of the squat exercise and compare the effects to the effects to using a rigid barbell (RB). A two-by-two repeated measures Analysis of Variance (ANOVA) test was used to compare the results. Descriptive statistics showed significantly higher GRFs for the TB during the unweighting phase, significant differences in GRFs between speeds for each phase, significantly higher forces on average with the …