An automatic diagnostic system for the urodynamic study applying in lower urinary tract dysfunction.

Objective: To establish an automatic diagnostic system based on machine learning for preliminarily analysis of urodynamic study applying in lower urinary tract dysfunction (LUTD).

Methods: The eight most common conditions of LUTDs were included in the present study. A total of 527 eligible patients with complete data, from the year of 2015 to 2020, were enrolled in this study.

DAIS: Automatic Channel Pruning via Differentiable Annealing Indicator Search.

The convolutional neural network (CNN) has achieved great success in fulfilling computer vision tasks despite large computation overhead against efficient deployment. Channel pruning is usually applied to reduce the model redundancy while preserving the network structure, such that the pruned network can be easily deployed in practice. However, existing channel pruning methods require hand-crafted rules, which can result in a degraded model performance with respect to the tremendous potential pruning space given large neural networks.

Scalp-recorded high-frequency oscillations in childhood epileptic encephalopathy with continuous spike-and-wave during sleep with different etiologies.

Objective: To investigate high-frequency oscillations (HFOs) in epileptic encephalopathy with continuous spike-and-wave during sleep (CSWS) with different etiologies.

Methods: Twenty-one CSWS patients treated with methylprednisolone were divided into structural group and genetic/unknown group. Comparisons were made between the two etiological groups: selected clinical variables including gender, age parameters, seizure frequencies and antiepileptic drugs; distribution of HFOs in pre-methylprednisolone electroencephalography (EEG) and percentage changes of HFOs and spikes after methylprednisolone treatment.

WE-CARE: an intelligent mobile telecardiology system to enable mHealth applications.

Recently, cardiovascular disease (CVD) has become one of the leading death causes worldwide, and it contributes to 41% of all deaths each year in China. This disease incurs a cost of more than 400 billion US dollars in China on the healthcare expenditures and lost productivity during the past ten years. It has been shown that the CVD can be effectively prevented by an interdisciplinary approach that leverages the technology development in both IT and electrocardiogram (ECG) fields.