AIMC Topic: Heart Diseases
Clear Filters Showing 151 to 160 of 198 articles
Predicting Survival From Large Echocardiography and Electronic Health Record Datasets: Optimization With Machine Learning.
JACC. Cardiovascular imaging
Jun 13, 2018
OBJECTIVES: The goal of this study was to use machine learning to more accurately predict survival after echocardiography.
Heart disease diagnosis based on mediative fuzzy logic.
Artificial intelligence in medicine
May 30, 2018
Mediative fuzzy logic is an approach able to deal with inconsistent information providing a solution when contradiction exists. The aim of this paper is to design an expert system based on this type of fuzzy logic in order to diagnose a possible hear...
Prediction of radiographic abnormalities by the use of bag-of-features and convolutional neural networks.
Veterinary journal (London, England : 1997)
May 29, 2018
This study evaluated the feasibility of bag-of-features (BOF) and convolutional neural networks (CNN) for computer-aided detection in distinguishing normal from abnormal radiographic findings. Computed thoracic radiographs of dogs were collected. For...
Deep Learning Techniques for Automatic MRI Cardiac Multi-Structures Segmentation and Diagnosis: Is the Problem Solved?
IEEE transactions on medical imaging
May 17, 2018
Delineation of the left ventricular cavity, myocardium, and right ventricle from cardiac magnetic resonance images (multi-slice 2-D cine MRI) is a common clinical task to establish diagnosis. The automation of the corresponding tasks has thus been th...
Segmentation of histological images and fibrosis identification with a convolutional neural network.
Computers in biology and medicine
May 16, 2018
Segmentation of histological images is one of the most crucial tasks for many biomedical analyses involving quantification of certain tissue types, such as fibrosis via Masson's trichrome staining. However, challenges are posed by the high variabilit...
Determining post-test risk in a national sample of stress nuclear myocardial perfusion imaging reports: Implications for natural language processing tools.
Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
Apr 25, 2018
BACKGROUND: Reporting standards promote clarity and consistency of stress myocardial perfusion imaging (MPI) reports, but do not require an assessment of post-test risk. Natural Language Processing (NLP) tools could potentially help estimate this ris...
Sliding to predict: vision-based beating heart motion estimation by modeling temporal interactions.
International journal of computer assisted radiology and surgery
Jan 19, 2018
PURPOSE: Technical advancements have been part of modern medical solutions as they promote better surgical alternatives that serve to the benefit of patients. Particularly with cardiovascular surgeries, robotic surgical systems enable surgeons to per...
ν-net: Deep Learning for Generalized Biventricular Mass and Function Parameters Using Multicenter Cardiac MRI Data.
JACC. Cardiovascular imaging
Jan 17, 2018
Multi-Views Fusion CNN for Left Ventricular Volumes Estimation on Cardiac MR Images.
IEEE transactions on bio-medical engineering
Oct 13, 2017
OBJECTIVE: Left ventricular (LV) volume estimation is a critical procedure for cardiac disease diagnosis. The objective of this paper is to address a direct LV volume prediction task.
Early hospital mortality prediction of intensive care unit patients using an ensemble learning approach.
International journal of medical informatics
Oct 5, 2017
BACKGROUND: Mortality prediction of hospitalized patients is an important problem. Over the past few decades, several severity scoring systems and machine learning mortality prediction models have been developed for predicting hospital mortality. By ...
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