BACKGROUND: This study aimed to train, validate and compare predictive models that use machine learning analysis for good neurological recovery in OHCA patients.
OBJECTIVES: This study sought to develop a fully automated framework for cardiac function analysis from cardiac magnetic resonance (CMR), including comprehensive quality control (QC) algorithms to detect erroneous output.
Biomedical repositories such as the UK Biobank provide increasing access to prospectively collected cardiac imaging, however these data are unlabeled, which creates barriers to their use in supervised machine learning. We develop a weakly supervised ...
IEEE journal of biomedical and health informatics
Jun 11, 2019
Constructing statistical models using personal sensor data could allow for tracking health status over time, thereby enabling the possibility of early intervention. The goal of this study was to use machine learning algorithms to classify patient-rep...
We propose a method to classify cardiac pathology based on a novel approach to extract image derived features to characterize the shape and motion of the heart. An original semi-supervised learning procedure, which makes efficient use of a large amou...
Computer methods and programs in biomedicine
May 29, 2019
BACKGROUND AND OBJECTIVE: Atrial fibrillation (AF) is one of the common cardiovascular diseases, and electrocardiography (ECG) is a key indicator for the detection and diagnosis of AF and other heart diseases. In this study, an improved machine learn...
Clinical narratives are a valuable source of information for both patient care and biomedical research. Given the unstructured nature of medical reports, specific automatic techniques are required to extract relevant entities from such texts. In the ...
Heart disease is a malignant threat to human health. Electrocardiogram (ECG) tests are used to help diagnose heart disease by recording the heart's activity. However, automated medical-aided diagnosis with computers usually requires a large volume of...
Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
Mar 15, 2019
OBJECTIVE: The fields of medicine and public health are undergoing a data revolution. An increasing availability of data has brought about a growing interest in machine-learning algorithms. Our objective is to present the reader with an introduction ...
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...