AIMC Topic: Atrophy
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Interpretable and Intuitive Machine Learning Approaches for Predicting Disability Progression in Relapsing-Remitting Multiple Sclerosis Based on Clinical and Gray Matter Atrophy Indicators.
Academic radiology
Feb 29, 2024
RATIONALE AND OBJECTIVES: To investigate whether clinical and gray matter (GM) atrophy indicators can predict disability in relapsing-remitting multiple sclerosis (RRMS) and to enhance the interpretability and intuitiveness of a predictive machine le...
Determination of Alzheimer's disease based on morphology and atrophy using machine learning combined with automated segmentation.
Acta radiologica (Stockholm, Sweden : 1987)
Jan 9, 2024
BACKGROUND: To evaluate the degree of cerebral atrophy for Alzheimer's disease (AD), voxel-based morphometry has been performed with magnetic resonance imaging. Detailed morphological changes in a specific tissue area having the most evidence of atro...
Suitability of machine learning for atrophy and fibrosis development in neovascular age-related macular degeneration.
Acta ophthalmologica
Dec 22, 2023
PURPOSE: To assess the suitability of machine learning (ML) techniques in predicting the development of fibrosis and atrophy in patients with neovascular age-related macular degeneration (nAMD), receiving anti-VEGF treatment over a 36-month period.
Ranibizumab
Machine Learning
Wet Macular Degeneration
Retrospective Studies
Atrophy
Humans
Visual Acuity
Tomography, Optical Coherence
Fundus Oculi
Intravitreal Injections
Fluorescein Angiography
Vascular Endothelial Growth Factor A
Fibrosis
Male
Angiogenesis Inhibitors
Follow-Up Studies
Female
Aged
Aged, 80 and over
Diagnosing and grading gastric atrophy and intestinal metaplasia using semi-supervised deep learning on pathological images: development and validation study.
Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association
Dec 14, 2023
OBJECTIVE: Patients with gastric atrophy and intestinal metaplasia (IM) were at risk for gastric cancer, necessitating an accurate risk assessment. We aimed to establish and validate a diagnostic approach for gastric biopsy specimens using deep learn...
Deep learning model for automatic differentiation of EMAP from AMD in macular atrophy.
Scientific reports
Nov 21, 2023
To create a deep learning (DL) classifier pre-trained on fundus autofluorescence (FAF) images that can assist the clinician in distinguishing age-related geographic atrophy from extensive macular atrophy and pseudodrusen-like appearance (EMAP). Patie...
Voxel-based morphometry in single subjects without a scanner-specific normal database using a convolutional neural network.
European radiology
Nov 9, 2023
OBJECTIVES: Reliable detection of disease-specific atrophy in individual T1w-MRI by voxel-based morphometry (VBM) requires scanner-specific normal databases (NDB), which often are not available. The aim of this retrospective study was to design, trai...
Objective analysis of partial three-dimensional rotator cuff muscle volume and fat infiltration across ages and sex from clinical MRI scans.
Scientific reports
Sep 1, 2023
Objective analysis of rotator cuff (RC) atrophy and fatty infiltration (FI) from clinical MRI is limited by qualitative measures and variation in scapular coverage. The goals of this study were to: develop/evaluate a method to quantify RC muscle size...
Deep learning to detect macular atrophy in wet age-related macular degeneration using optical coherence tomography.
Scientific reports
May 22, 2023
Here, we have developed a deep learning method to fully automatically detect and quantify six main clinically relevant atrophic features associated with macular atrophy (MA) using optical coherence tomography (OCT) analysis of patients with wet age-r...
Remote assessment of cognition and quality of life following radiotherapy for glioma: deep-learning-based predictive models and MRI correlates.
Journal of neuro-oncology
Apr 4, 2023
BACKGROUND: Glioma irradiation often unavoidably damages the brain volume and affects cognition. This study aims to evaluate the relationship of remote cognitive assessments in determining cognitive impairment of irradiated glioma patients in relatio...
Detection of duodenal villous atrophy on endoscopic images using a deep learning algorithm.
Gastrointestinal endoscopy
Jan 13, 2023
BACKGROUND AND AIMS: Celiac disease with its endoscopic manifestation of villous atrophy (VA) is underdiagnosed worldwide. The application of artificial intelligence (AI) for the macroscopic detection of VA at routine EGD may improve diagnostic perfo...
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