AIMC Topic: Retrospective Studies

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Development of Deep Learning Models to Predict Best-Corrected Visual Acuity from Optical Coherence Tomography.

Translational vision science & technology
PURPOSE: To develop deep learning (DL) models to predict best-corrected visual acuity (BCVA) from optical coherence tomography (OCT) images from patients with neovascular age-related macular degeneration (nAMD).

Quantitative retrospective natural history modeling for orphan drug development.

Journal of inherited metabolic disease
The natural history of most rare diseases is incompletely understood and usually relies on studies with low level of evidence. Consistent with the goals for future research of rare disease research set by the International Rare Diseases Research Cons...

MRI-visible dilated perivascular spaces in healthy young adults: A twin heritability study.

Human brain mapping
We investigated the narrow-sense heritability of MRI-visible dilated perivascular spaces (dPVS) in healthy young adult twins and nontwin siblings (138 monozygotic, 79 dizygotic twin pairs, and 133 nontwin sibling pairs; 28.7 ± 3.6 years) from the Hum...

Radiomic Model for Distinguishing Dissecting Aneurysms from Complicated Saccular Aneurysms on high-Resolution Magnetic Resonance Imaging.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
OBJECTIVE: To build radiomic model in differentiating dissecting aneurysm (DA) from complicated saccular aneurysm (SA) based on high-resolution magnetic resonance imaging (HR-MRI) through machine-learning algorithm.

Comparison of iterative parametric and indirect deep learning-based reconstruction methods in highly undersampled DCE-MR Imaging of the breast.

Medical physics
PURPOSE: To compare the performance of iterative direct and indirect parametric reconstruction methods with indirect deep learning-based reconstruction methods in estimating tracer-kinetic parameters from highly undersampled DCE-MR Imaging breast dat...

Improving preoperative risk-of-death prediction in surgery congenital heart defects using artificial intelligence model: A pilot study.

PloS one
BACKGROUND: Congenital heart disease accounts for almost a third of all major congenital anomalies. Congenital heart defects have a significant impact on morbidity, mortality and health costs for children and adults. Research regarding the risk of pr...