AIMC Topic: Reproducibility of Results

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Deep learning based automated left atrial segmentation and flow quantification of real time phase contrast MRI in patients with atrial fibrillation.

The international journal of cardiovascular imaging Apr 29, 2025
Real time 2D phase contrast (RTPC) MRI is useful for flow quantification in atrial fibrillation (AF) patients, but data analysis requires time-consuming anatomical contouring for many cardiac time frames. Our goal was to develop a convolutional neura...
Automation Blood Flow Velocity Atrial Function, Left Magnetic Resonance Imaging, Cine Deep Learning Time Factors Magnetic Resonance Imaging Predictive Value of Tests Heart Rate Image Interpretation, Computer-Assisted Observer Variation Atrial Fibrillation Reproducibility of Results Heart Atria Aged Male Middle Aged Humans Female
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Artificial intelligence-assisted left ventricular global longitudinal strain assessment in patients with acute myocardial infarction: a RESUS-AMI trial sub-analysis.

The international journal of cardiovascular imaging Apr 29, 2025
PURPOSE: The aim of this sub-analysis of the RESUS-AMI trial was to evaluate the correlation of artificial intelligence (AI)-assisted echocardiographic global longitudinal strain (GLS) assessments with infarct size, left ventricular ejection fraction...
Magnetic Resonance Imaging, Cine Myocardial Contraction Global Longitudinal Strain ST Elevation Myocardial Infarction Percutaneous Coronary Intervention Image Interpretation, Computer-Assisted Observer Variation Aged Male Ventricular Function, Left Stroke Volume Echocardiography Middle Aged Treatment Outcome Predictive Value of Tests Humans Artificial Intelligence Female Reproducibility of Results
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Integrating prior knowledge with deep learning for optimized quality control in corneal images: A multicenter study.

Computer methods and programs in biomedicine Apr 28, 2025
OBJECTIVE: Artificial intelligence (AI) models are effective for analyzing high-quality slit-lamp images but often face challenges in real-world clinical settings due to image variability. This study aims to develop and evaluate a hybrid AI-based ima...
Cornea Deep Learning Image Processing, Computer-Assisted Telemedicine Artificial Intelligence Algorithms Reproducibility of Results Cross-Sectional Studies Humans Quality Control
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Structural uncertainty estimation for medical image segmentation.

Medical image analysis Apr 28, 2025
Precise segmentation and uncertainty estimation are crucial for error identification and correction in medical diagnostic assistance. Existing methods mainly rely on pixel-wise uncertainty estimations. They (1) neglect the global context, leading to ...
Reproducibility of Results Ultrasonography Image Processing, Computer-Assisted Humans Image Interpretation, Computer-Assisted Neural Networks, Computer Uncertainty Algorithms
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Evaluating the Chinese versions of delirium assessment scales: a diagnostic systematic review.

BMC psychiatry Apr 28, 2025
BACKGROUND: The purpose of this study is to examine the validity, reliability and methodological quality of delirium scales that have been translated and adapted in China using quality assessment tools.
Humans Delirium Translations Reproducibility of Results Psychiatric Status Rating Scales China
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Research on noninvasive electrophysiologic imaging based on cardiac electrophysiology simulation and deep learning methods for the inverse problem.

BMC cardiovascular disorders Apr 28, 2025
BACKGROUND: The risk stratification and prognosis of cardiac arrhythmia depend on the individual condition of patients, while invasive diagnostic methods may be risky to patient health, and current non-invasive diagnostic methods are applicable to fe...
Humans Neural Networks, Computer Computer Simulation Arrhythmias, Cardiac Deep Learning Reproducibility of Results Models, Cardiovascular Heart Rate Electrocardiography Body Surface Potential Mapping Action Potentials Electrophysiologic Techniques, Cardiac Predictive Value of Tests
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Intraocular lens calculation formula developed using artificial intelligence for ultrasonic biometry.

Arquivos brasileiros de oftalmologia Apr 28, 2025
PURPOSE: We developed an artificial intelligence program for calculating intraocular lenses and analyzed its accuracy rate via ultrasonic biometry. This endeavor is aimed at enhancing precision and efficacy in the selection of intraocular lenses, par...
Female Reproducibility of Results Humans Aged Adult Lenses, Intraocular Artificial Intelligence Aged, 80 and over Male Phacoemulsification Middle Aged Biometry Refraction, Ocular Lens Implantation, Intraocular
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Application and optimization of the U-Net++ model for cerebral artery segmentation based on computed tomographic angiography images.

European journal of radiology Apr 27, 2025
Accurate segmentation of cerebral arteries on computed tomography angiography (CTA) images is essential for the diagnosis and management of cerebrovascular diseases, including ischemic stroke. This study implemented a deep learning-based U-Net++ mode...
Reproducibility of Results Deep Learning Radiographic Image Interpretation, Computer-Assisted Cerebrovascular Disorders Computed Tomography Angiography Cerebral Angiography Cerebral Arteries Humans
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Fast and automatic coronary artery segmentation using nnU-Net for non-contrast enhanced magnetic resonance coronary angiography.

The international journal of cardiovascular imaging Apr 26, 2025
Non-contrast enhanced magnetic resonance coronary angiography (MRCA) is a promising coronary heart disease screening modality. However, its clinical application is hindered by inherent limitations, including low spatial resolution and insufficient co...
Humans Middle Aged Deep Learning Time Factors Predictive Value of Tests Coronary Angiography Female Reproducibility of Results Aged Male Coronary Vessels Magnetic Resonance Angiography Computed Tomography Angiography Coronary Artery Disease Image Interpretation, Computer-Assisted Observer Variation Automation
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Optimising coronary imaging decisions with machine learning: an external validation study.

Open heart Apr 24, 2025
BACKGROUND: Exclusion of coronary stenosis in individuals with suggestive symptoms is challenging. Cardiac CT or coronary angiography is often used but is inefficient and costly and involves risks. Sex-stratified algorithms based on electronic health...
Male Middle Aged Predictive Value of Tests Coronary Angiography Coronary Artery Disease Netherlands Sex Factors Coronary Vessels Electronic Health Records Female Reproducibility of Results Aged Humans Computed Tomography Angiography Machine Learning Coronary Stenosis Algorithms Retrospective Studies
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