Weakly-supervised learning based on, e.g., partially labelled images or image-tags, is currently attracting significant attention in CNN segmentation as it can mitigate the need for full and laborious pixel/voxel annotations. Enforcing high-order (gl...
Forensic science international. Genetics
Feb 13, 2019
For several decades, a common approach for processing sexual assault evidence has been to use the "standard" differential extraction to separate the evidence into a non-sperm-cell fraction and a sperm-cell fraction for further analysis. In this stand...
Alimentary pharmacology & therapeutics
Feb 13, 2019
BACKGROUND: Patients with a history of Helicobacter pylori-negative idiopathic bleeding ulcers have an increased risk of recurring ulcer complications.
INTRODUCTION: This study aims to obtain data on the prevalence and incidence of structural heart disease in a population setting and, to analyse and present those data on the application of spatial and machine learning methods that, although known to...
Pressure ulcers, by definition, are caused by external forces on the tissues, often in the regions of bony prominences. Wheelchair users are at risk to develop sitting-acquired pressure ulcers, which occur in the regions of the ischial tuberosities, ...
OBJECTIVE: To determine the possible influence of segmentation margin on each step (feature reproducibility, selection, and classification) of the machine learning (ML)-based high-dimensional quantitative computed tomography (CT) texture analysis (qC...
OBJECTIVES: Distinguishing between kidney stones and phleboliths can constitute a diagnostic challenge in patients undergoing unenhanced low-dose CT (LDCT) for acute flank pain. We sought to investigate the accuracy of radiomics and a machine-learnin...
OBJECTIVES: Stereotactic radiosurgery (SRS) is a minimally invasive modality for the treatment of trigeminal neuralgia (TN). Outcome prediction of this modality is very important for proper case selection. The aim of this study was to create artifici...
Traditional methods for assessing illness severity and predicting in-hospital mortality among critically ill patients require time-consuming, error-prone calculations using static variable thresholds. These methods do not capitalize on the emerging a...
Recent popular claims surrounding virtual assistants suggest that computers will soon be able to hear our emotions. Supporting this possibility, promising work has harnessed big data and emergent technologies to automatically predict stable levels of...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.