AIMC Topic: Predictive Value of Tests

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Direct Risk Assessment From Myocardial Perfusion Imaging Using Explainable Deep Learning.

JACC. Cardiovascular imaging
BACKGROUND: Myocardial perfusion imaging (MPI) is frequently used to provide risk stratification, but methods to improve the accuracy of these predictions are needed.

Deep-Learning-Based Representation of Vocal Fold Dynamics in Adductor Spasmodic Dysphonia during Connected Speech in High-Speed Videoendoscopy.

Journal of voice : official journal of the Voice Foundation
OBJECTIVE: Adductor spasmodic dysphonia (AdSD) is a neurogenic dystonia, which causes spasms of the laryngeal muscles. This disorder mainly affects production of connected speech. To understand how AdSD affects vocal fold (VF) movements and hence, th...

Comparison of three machine learning models to predict suicidal ideation and depression among Chinese adolescents: A cross-sectional study.

Journal of affective disorders
BACKGROUND: Machine learning (ML) algorithms based on various clinicodemographic, psychometric, and biographic factors have been used to predict depression, suicidal ideation, and suicide attempt in adolescents, but there is still a need for more acc...

Deep Learning of Coronary Calcium Scores From PET/CT Attenuation Maps Accurately Predicts Adverse Cardiovascular Events.

JACC. Cardiovascular imaging
BACKGROUND: Assessment of coronary artery calcium (CAC) by computed tomographic (CT) imaging provides an accurate measure of atherosclerotic burden. CAC is also visible in computed tomographic attenuation correction (CTAC) scans, always acquired with...

A SuperLearner Approach to Predict Run-In Selection in Clinical Trials.

Computational and mathematical methods in medicine
A critical early step in a clinical trial is defining the study sample that appropriately represents the target population from which the sample will be drawn. Envisaging a "run-in" process in study design may accomplish this task; however, the tradi...

An Automated View Classification Model for Pediatric Echocardiography Using Artificial Intelligence.

Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography
BACKGROUND: View classification is a key step toward building a fully automated system for interpretation of echocardiograms. However, compared with adult echocardiograms, creating a view classification model for pediatric echocardiograms poses addit...

Systematic comparison of machine learning algorithms to develop and validate predictive models for periodontitis.

Journal of clinical periodontology
AIM: The aim of this study was to compare the validity of different machine learning algorithms to develop and validate predictive models for periodontitis.

Great debates in cardiac computed tomography: OPINION: "Artificial intelligence and the future of cardiovascular CT - Managing expectation and challenging hype".

Journal of cardiovascular computed tomography
This manuscript has been written as a follow-up to the "AI/ML great debate" featured at the 2021 Society of Cardiovascular Computed Tomography (SCCT) Annual Scientific Meeting. In debate style, we highlighti the need for expectation management of AI/...