ABSTRACT
Despite embolization being now considered the preferred treatment for PAVM, surgical intervention may be considered if the malformation involves large vessels.
ABSTRACT
Electroencephalographic (EEG) data is considered contaminated with various types of artifacts. Deep learning has been successfully applied to developing EEG artifact removal techniques to increase the signal-to-noise ratio (SNR) and enhance brain-computer interface performance. Recently, our research team has proposed an end-to-end UNet-based EEG artifact removal technique, IC-U-Net, which can reconstruct signals against various artifacts. However, this model suffers from being prone to overfitting with a limited training dataset size and demanding a high computational cost. To address these issues, this study attempted to leverage the architecture of UNet++ to improve the practicability of IC-U-Net by introducing dense skip connections in the encoder-decoder architecture. Results showed that this proposed model obtained superior SNR to the original model with half the number of parameters. Also, this proposed model achieved comparable convergency using a quarter of the training data size.
Subject(s)
Artifacts , Brain-Computer Interfaces , Algorithms , Electroencephalography/methods , Signal-To-Noise RatioABSTRACT
Situs ambiguus is a rare congenital abnormality with outcomes ranging from asymptomatic to fatal. Here we present a woman with an incidental finding of situs ambiguus hinted by her chest radiograph. This case highlights the importance of actively seeking diagnosis when right sub-diaphragmic air is noted when viewing a chest radiograph.
Subject(s)
COVID-19 , Respiratory Insufficiency , Cannula , Humans , Oxygen Inhalation Therapy , Respiratory Insufficiency/therapy , SARS-CoV-2ABSTRACT
Chronic obstructive pulmonary disease (COPD) is a chronic respiratory disease that reduces lung and respiratory function, with a high mortality rate. Severe and acute deterioration of COPD can easily lead to respiratory failure, resulting in personal, social, and medical burden. Recent studies have shown a high correlation between the gut microbiota and lung inflammation. In this study, we investigated the relationship between gut microbiota and COPD severity. A total of 60 COPD patients with varying severity according to GOLD guidelines were enrolled in this study. DNA was extracted from patients' stool and 16S rRNA data analysis conducted using high-throughput sequencing followed by bioinformatics analysis. The richness of the gut microbiota was not associated with COPD severity. The gut microbiome is more similar in stage 1 and 2 COPD than stage 3+4 COPD. Fusobacterium and Aerococcus were more abundant in stage 3+4 COPD. Ruminococcaceae NK4A214 group and Lachnoclostridium were less abundant in stage 2-4, and Tyzzerella 4 and Dialister were less abundant in stage 1. However, the abundance of a Bacteroides was associated with blood eosinophils and lung function. This study suggests that no distinctive gut microbiota pattern is associated with the severity of COPD. The gut microbiome could affect COPD by gut inflammation shaping the host immune system.