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Full-Text Articles in Biostatistics
Characterizing The Effects Of Repetitive Head Trauma In Female Soccer Athletes For Prevention Of Mild Traumatic Brain Injury, Diana Otero Svaldi
Characterizing The Effects Of Repetitive Head Trauma In Female Soccer Athletes For Prevention Of Mild Traumatic Brain Injury, Diana Otero Svaldi
Open Access Dissertations
As participation in women’s soccer continues to grow and the longevity of female athletes’ careers continues to increase, prevention of mTBI in women’s soccer has become a major concern for female athletes as the long-term risks associated with a history of mTBI are well documented. Among women’s sports, soccer exhibits the highest concussion rates, on par with those of men’s football at the collegiate level. Head impact monitoring technology has revealed that “concussive hits” occurring directly before symptomatic injury are not predictive of mTBI, suggesting that the cumulative effect of repetitive head impacts experienced by collision sport athletes should be …
Is Metabolism Goal-Directed? Investigating The Validity Of Modeling Biological Systems With Cybernetic Control Via Omic Data, Frank T. Devilbiss
Is Metabolism Goal-Directed? Investigating The Validity Of Modeling Biological Systems With Cybernetic Control Via Omic Data, Frank T. Devilbiss
Open Access Dissertations
Cybernetic models are uniquely juxtaposed to other metabolic modeling frameworks in that they describe the time-dependent regulation of cellular reactions in terms of dynamic "metabolic goals." This approach contrasts starkly with purely mechanistic descriptions of metabolic regulation which seek to explain metabolic processes in high resolution — a clearly daunting undertaking. Over a span of three decades, cybernetic models have been used to predict metabolic phenomena ranging from resource consumption in mixed-substrate environments to intracellular reaction fluxes of intricate metabolic networks. While the cybernetic approach has been validated in its utility for the prediction of metabolic phenomena, its central feature, …
Bottom-Up Design Of Artificial Neural Network For Single-Lead Electrocardiogram Beat And Rhythm Classification, Srikanth Thiagarajan
Bottom-Up Design Of Artificial Neural Network For Single-Lead Electrocardiogram Beat And Rhythm Classification, Srikanth Thiagarajan
Doctoral Dissertations
Performance improvement in computerized Electrocardiogram (ECG) classification is vital to improve reliability in this life-saving technology. The non-linearly overlapping nature of the ECG classification task prevents the statistical and the syntactic procedures from reaching the maximum performance. A new approach, a neural network-based classification scheme, has been implemented in clinical ECG problems with much success. The focus, however, has been on narrow clinical problem domains and the implementations lacked engineering precision. An optimal utilization of frequency information was missing. This dissertation attempts to improve the accuracy of neural network-based single-lead (lead-II) ECG beat and rhythm classification. A bottom-up approach defined …