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Utilizing a novel T1rho method to detect spinal degeneration via magnetic resonance imaging

Wang et al. | Oct 04, 2023

Utilizing a novel T1rho method to detect spinal degeneration via magnetic resonance imaging

Spinal degeneration has been linked to critical conditions such as osteoarthritis in adults aged 40+; while this condition is considered to be irreversible, we took interest in magnetic resonance imaging (MRI) for early detection of the condition. Ultimately, our purpose was to determine the effectiveness of a relatively novel T1rho method in the early detection of spinal degeneration, and we hypothesized that the early to mild progression of spinal degeneration would affect T1rho values following an MRI scan.

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Collaboration beats heterogeneity: Improving federated learning-based waste classification

Chong et al. | Jul 18, 2023

Collaboration beats heterogeneity: Improving federated learning-based waste classification

Based on the success of deep learning, recent works have attempted to develop a waste classification model using deep neural networks. This work presents federated learning (FL) for a solution, as it allows participants to aid in training the model using their own data. Results showed that with less clients, having a higher participation ratio resulted in less accuracy degradation by the data heterogeneity.

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A comparison of use of the mobile electronic health record by medical providers based on clinical setting

Stover et al. | Jul 12, 2023

A comparison of use of the mobile electronic health record by medical providers based on clinical setting
Image credit: Tima Miroshnichenko

The electronic health record (EHR), along with its mobile application, has demonstrated the ability to improve the efficiency and accuracy of health care delivery. This study included data from 874 health care providers over a 12-month period regarding their usage of mobile phone (EPIC® Haiku) and tablet (EPIC® Canto) mEHR. Ambulatory and inpatient care providers had the greatest usage levels over the 12-month period. Awareness of workflow allows for optimization of mEHR design and implementation, which should increase mEHR adoption and usage, leading to better health outcomes for patients.

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