Pulmonary hypertension (PH) is a serious prognostic complication in patients with systemic sclerosis (SSc). Deep learning models can be applied to detect PH in the chest X-ray images of these patients. The aim of the study was to investigate the perf...
Left ventricular dilatation (LVD) and left ventricular hypertrophy (LVH) are risk factors for heart failure, and their detection improves heart failure screening. This study aimed to investigate the ability of deep learning to detect LVD and LVH from...
The development of deep learning technology has enabled machines to achieve high-level accuracy in interpreting medical images. While many previous studies have examined the detection of pulmonary nodules in chest X-rays using deep learning, the appl...
This study aimed to evaluate the feasibility and the mid-term efficacy of an in situ skeletonized right internal mammary artery (IMA) bypass grafting to a left anterior descending artery (LAD), and to determine risk factors for IMA graft failure in a...
Cardiac sympathetic nerve activity is known to play a key role in the development and progression of heart failure (HF). Azelnidipine, an L-type calcium channel blocker (CCB), inhibits the sympathetic nerve activity of the central system. In contrast...
Accurate prediction of echocardiographic parameters is essential for diagnosis and treatment of cardiac disease, especially for segmentation of the left ventricle to obtain measurements such as left ventricular ejection fraction and volume. However, ...
Comprehensive management approaches for patients with ischemic heart disease (IHD) are important aids for prognostication and treatment planning. While single-modality deep neural networks (DNNs) have shown promising performance for detecting cardiac...
Several errors (shown with underlines) in the following list appeared in the article entitled "Automatic Detection of Left Ventricular Dilatation and Hypertrophy from Electrocardiograms Using Deep Learning" by Takahiro Kokubo, Satoshi Kodera, Shinnos...
Deep learning models can be applied to electrocardiograms (ECGs) to detect left ventricular (LV) dysfunction. We hypothesized that applying a deep learning model may improve the diagnostic accuracy of cardiologists in predicting LV dysfunction from E...