CapNet: An Automatic Attention-Based with Mixer Model for Cardiovascular Magnetic Resonance Image Segmentation.

Deep neural networks have shown excellent performance in medical image segmentation, especially for cardiac images. Transformer-based models, though having advantages over convolutional neural networks due to the ability of long-range dependence learning, still have shortcomings such as having a large number of parameters and and high computational cost. Additionally, for better results, they are often pretrained on a larger data, thus requiring large memory size and increasing resource expenses.

Comparative efficacy of antioxidant therapies for sepsis and septic shock in the intensive care unit: A frequentist network meta-analysis.

Background: Antioxidant therapy is gaining traction in managing sepsis and septic shock, owing to its perceived positive impact on patient outcomes. This study sought to compare the efficacy of five antioxidant therapies (melatonin, vitamin C, vitamin E, selenium, and -acetylcysteine, both individually and in combination with other compounds such as vitamin B1, hydrocortisone, propolis, and glutamine) in treating sepsis or septic shock in the intensive care unit (ICU).

Methods: The study involved randomized and multi-arm trials with sepsis or septic shock patients using melatonin, vitamin C, vitamin E, selenium, or -acetylcysteine.

Effects of proprioceptive training for people with stroke: A meta-analysis of randomized controlled trials.

Objective: To evaluate the effectiveness of proprioceptive training on balance performance, trunk control, and gait speed in people with stroke.

Methods: We searched PubMed, Science Direct, Cochrane, Embase, and Medline for randomized controlled trials that evaluated the effects of proprioceptive training for patients with stroke from the date of each database's inception to July 26, 2021. Two reviewers independently screened the titles and abstracts of potentially eligible articles that were identified on the basis of the search criteria.

EAR-UNet: A deep learning-based approach for segmentation of tympanic membranes from otoscopic images.

This paper presents a method for automatic segmentation of tympanic membranes (TMs) from video-otoscopic images based on deep fully convolutional neural network. Built upon the UNet architecture, the proposed EAR scheme is based on three main paradigms: EfficientNet for the encoder, Attention gate for the skip connection path, and Residual blocks for the decoder. The paper also introduces a new loss function term for the neural networks to perform segmentation tasks.

Effects of self-management programs on blood pressure, self-efficacy, medication adherence and body mass index in older adults with hypertension: Meta-analysis of randomized controlled trials.

Aim: To assess the effects of self-management interventions on systolic blood pressure, diastolic blood pressure, self-efficacy, medication adherence and body mass index in older adults with hypertension.

Background: Effective treatment of hypertension may require the practice of self-management behaviours. However, evidence on effects of self-management interventions on blood pressure, self-efficacy, medication adherence and body mass index in older adults with hypertension is lacking.

Psychometric Properties and Factorial Structure of Vietnamese Version of the Hypertension Self-care Profile Behavior Scale.

Background: The Hypertension Self-care Profile Behavior (HTN-SCPB) scale is a self-report instrument with which a patient's self-care behavior can be assessed. However, its psychometric properties for adult patients with hypertension in Vietnam require clarification.

Objective: The aim of this study was to translate the HTN-SCPB scale into Vietnamese and to assess its psychometric properties.

Sexual awareness and cognitive social capital among high school students: a cross-sectional study in rural Vietnam.

Since the late 1980s, Vietnam has seen numerous social changes, likely leading to changes in adolescent sexual awareness. Adolescents are currently exposed to a plethora of sexual information without adequate sex education and knowledge. Globally, researchers have identified sexual knowledge and self-esteem as determinants of adolescent sexual awareness and behavior, but little is known about the role of social capital, especially in rural areas.

Predicting ventricular tachyarrhythmia in patients with systolic heart failure based on texture features of the gray zone from contrast-enhanced magnetic resonance imaging.

Background: Previous research showed that gray zone detected by late gadolinium enhancement cardiovascular magnetic resonance (LGE-CMR) imaging could help identify high-risk patients. In this study, we investigated whether LGE-CMR gray zone heterogeneity measured by image texture features could predict cardiovascular events in patients with heart failure (HF).

Method: This is a retrospective cohort study.

Effects of Patient Activation Intervention on Chronic Diseases: A Meta-Analysis.

Background: Patient activation has been described as a potential strategy to improve chronic disease self-management. However, the effects of patient activation interventions on psychological and behavioral outcomes have not been systematically evaluated.

Purpose: This study was designed to evaluate the effects of patient activation interventions on physiological, psychological, behavioral, and health-related quality of life outcomes in patients with chronic diseases.

Probing age-related changes in cardio-respiratory dynamics by multimodal coupling assessment.

Quantifying respiratory sinus arrhythmia (RSA) can provide an index of parasympathetic function. Fourier spectral analysis, the most widely used approach, estimates the power of the heart rate variability in the frequency band of breathing. However, it neglects the time-varying characteristics of the transitions as well as the nonlinear properties of the cardio-respiratory coupling.

Development of an Automatic Diagnostic Algorithm for Pediatric Otitis Media.

Hypothesis: The artificial intelligence and image processing technology can develop automatic diagnostic algorithm for pediatric otitis media (OM) with accuracy comparable to that from well-trained otologists.

Background: OM is a public health issue that occurs commonly in pediatric population. Caring for OM may incur significant indirect cost that stems mainly from loss of school or working days seeking for medical consultation.

Empirical Mode Decomposition and Monogenic Signal-Based Approach for Quantification of Myocardial Infarction From MR Images.

Quantification of myocardial infarction on late Gadolinium enhancement cardiovascular magnetic resonance (LGE-CMR) images into heterogeneous infarct periphery (or gray zone) and infarct core plays an important role in cardiac diagnosis, especially in identifying patients at high risk of cardiovascular mortality. However, quantification task is challenging due to noise corrupted in cardiac MR images, the contrast variation, and limited resolution of images. In this study, we propose a novel approach for automatic myocardial infarction quantification, termed DEMPOT, which consists of three key parts: Decomposition of image into intrinsic modes, monogenic phase performing on combined dominant modes, and multilevel Otsu thresholding on the phase.

Endocardial Remodeling in Heart Failure Patients with Impaired and Preserved Left Ventricular Systolic Function--A Magnetic Resonance Image Study.

Left ventricular (LV) trabeculation has been studied in certain forms of cardiomyopathy. However, the changes of LV endocardial trabeculation during the remodeling process leading to heart failure (HF) are unclear. Seventy-four patients with systolic heart failure (SHF), 65 with heart failure with preserved ejection fraction (HFpEF) and 61 without HF were prospectively enrolled.

Acoustic-integrated dynamic MR imaging for a patient with obstructive sleep apnea.

Obstructive sleep apnea syndrome (OSAS) is caused by multi-level upper airway obstruction. Anatomic changes at the sites of obstruction may modify the physical or acoustic properties of snores. The surgical success of OSA depends upon precise localization of obstructed levels.

Synchronized imaging and acoustic analysis of the upper airway in patients with sleep-disordered breathing.

Progressive narrowing of the upper airway increases airflow resistance and can produce snoring sounds and apnea/hypopnea events associated with sleep-disordered breathing due to airway collapse. Recent studies have shown that acoustic properties during snoring can be altered with anatomic changes at the site of obstruction. To evaluate the instantaneous association between acoustic features of snoring and the anatomic sites of obstruction, a novel method was developed and applied in nine patients to extract the snoring sounds during sleep while performing dynamic magnetic resonance imaging (MRI).