OBJECTIVE: The electrocardiogram (ECG) provides an effective, non-invasive approach for clinical diagnosis in patients with cardiac diseases such as atrial fibrillation (AF). AF is the most common cardiac rhythm disturbance and affects ~2% of the gen...
OBJECTIVE: Structural MRI (sMRI) increasingly offers insight into abnormalities inherent to schizophrenia. Previous machine learning applications suggest that individual classification is feasible and reliable and, however, is focused on the predicti...
BACKGROUND: Application of deep-learning technology to skin cancer classification can potentially improve the sensitivity and specificity of skin cancer screening, but the number of training images required for such a system is thought to be extremel...
INTRODUCTION: Readmission from inpatient rehabilitation facilities to acute care hospitals is a serious problem. This study aims to develop a predictive model based on machine learning algorithms to identify patients at high risk of readmission.
PURPOSE: We sought to assess whether machine learning-based classification approaches can improve the classification of pancreatic tumor models relative to more simplistic analysis methods, using T relaxation, CEST, and DCE MRI.
BACKGROUND: How much anal sphincter dysfunction contributes to fecal incontinence (FI) is not clear. High-definition anorectal manometry (HDAM) and functional luminal imaging probe (Endoflip) are two new techniques to study anal sphincter function.
Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Sep 13, 2018
In Alzheimer's research, Mild Cognitive Impairment (MCI) is an important intermediate stage between normal aging and Alzheimer's. How to distinguish MCI samples that finally convert to AD from those do not is an essential problem in the prevention an...
Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Sep 13, 2018
Although alternations of brain functional networks (BFNs) derived from resting-state functional magnetic resonance imaging (rs-fMRI) have been considered as promising biomarkers for early Alzheimer's disease (AD) diagnosis, it is still challenging to...
Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Sep 13, 2018
Deep learning has become the new state-of-the-art for many problems in image analysis. However, large datasets are often required for such deep networks to learn effectively. This poses a difficult challenge for many medical image analysis problems i...
Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
Sep 12, 2018
OBJECTIVES: To describe and validate an artificial intelligence (AI)-driven structured reporting system by direct comparison of automatically generated reports to results from actual clinical reports generated by nuclear cardiology experts.
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.