Journal of gastroenterology and hepatology
Oct 13, 2023
BACKGROUND AND AIM: Convolutional neural network (CNN) systems that automatically detect abnormalities from small-bowel capsule endoscopy (SBCE) images are still experimental, and no studies have directly compared the clinical usefulness of different...
Successful treatment of pulmonary tuberculosis (TB) depends on early diagnosis and careful monitoring of treatment response. Identification of acid-fast bacilli by fluorescence microscopy of sputum smears is a common tool for both tasks. Microscopy-b...
BACKGROUND: Adaptive proton therapy workflows rely on accurate imaging throughout the treatment course. Our centre currently utilizes weekly repeat CTs (rCTs) for treatment monitoring and plan adaptations. However, deep learning-based methods have re...
International journal of neural systems
Oct 13, 2023
ConceFT (concentration of frequency and time) is a new time-frequency (TF) analysis method which combines multitaper technique and synchrosqueezing transform (SST). This combination produces highly concentrated TF representations with approximately p...
PURPOSE: Diffusion-weighted imaging (DWI) of the liver suffers from low resolution, noise, and artifacts. This study aimed to investigate the effect of deep learning reconstruction (DLR) on image quality and apparent diffusion coefficient (ADC) quant...
Journal of the American Heart Association
Oct 13, 2023
Background The success of cardiac auscultation varies widely among medical professionals, which can lead to missed treatments for structural heart disease. Applying machine learning to cardiac auscultation could address this problem, but despite rece...
BACKGROUND: Measurement of the left ventricular outflow tract diameter (LVOTd) in echocardiography is a common source of error when used to calculate the stroke volume. The aim of this study is to assess whether a deep learning (DL) model, trained on...
BACKGROUND: Alzheimer's disease (AD) is an incurable, debilitating neurodegenerative disorder. Current biomarkers for AD diagnosis require expensive neuroimaging or invasive cerebrospinal fluid sampling, thus precluding early detection. Blood-based b...
Placenta previa causes life-threatening bleeding and accurate prediction of severe hemorrhage leads to risk stratification and optimum allocation of interventions. We aimed to use a multimodal deep learning model to predict severe hemorrhage. Using M...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.