AIMC Topic: Predictive Value of Tests

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Reliability of respiratory-gated real-time two-dimensional cine incorporating deep learning reconstruction for the assessment of ventricular function in an adult population.

The international journal of cardiovascular imaging
This study aimed to assess the image quality and accuracy of respiratory-gated real-time two-dimensional (2D) cine incorporating deep learning reconstruction (DLR) for the quantification of biventricular volumes and function compared with those of th...

Prediction of Coronary Artery Calcium Using Deep Learning of Echocardiograms.

Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography
BACKGROUND: Coronary artery calcification (CAC), often assessed by computed tomography (CT), is a powerful marker of coronary artery disease that can guide preventive therapies. Computed tomographies, however, are not always accessible or serially ob...

A Machine Learning Model for Prediction of Amputation in Diabetics.

Journal of diabetes science and technology
BACKGROUND: Diabetic foot ulcer (DFU) and the resulting lower extremity amputation are associated with a poor survival prognosis. The objective of this study is to generate a model for predicting the probability of major amputation in hospitalized pa...

Cardiovascular magnetic resonance images with susceptibility artifacts: artificial intelligence with spatial-attention for ventricular volumes and mass assessment.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
BACKGROUND: Segmentation of cardiovascular magnetic resonance (CMR) images is an essential step for evaluating dimensional and functional ventricular parameters as ejection fraction (EF) but may be limited by artifacts, which represent the major chal...

Recognition of the Effect of Vocal Exercises by Fuzzy Triangular Naive Bayes, a Machine Learning Classifier: A Preliminary Analysis.

Journal of voice : official journal of the Voice Foundation
OBJECTIVES: Machine learning (ML) methods allow the development of expert systems for pattern recognition and predictive analysis of intervention outcomes. It has been used in Voice Sciences, mainly to discriminate between healthy and dysphonic voice...

Pathological Voice Detection Based on Phase Reconstitution and Convolutional Neural Network.

Journal of voice : official journal of the Voice Foundation
The nonlinear dynamic features can effectively describe the acoustic characteristics of normal and pathological voice. In this paper, the phase space reconstruction and convolution neural network are used to classify the normal and pathological voice...

Deep learning-based prediction of coronary artery stenosis resistance.

American journal of physiology. Heart and circulatory physiology
Coronary artery stenosis resistance (SR) is a key factor for noninvasive calculations of fractional flow reserve derived from coronary CT angiography (FFR). Existing computational fluid dynamics (CFD) methods, including three-dimensional (3-D) comput...

Current Applications of Robot-Assisted Ultrasound Examination.

JACC. Cardiovascular imaging
Despite advances in miniaturization and automation, the need for expert acquisition of a full echocardiogram, including Doppler, has restricted access in remote areas. Recent developments in robotics, teleoperation, and upgraded telecommunications in...