AIMC Topic: Prospective Studies
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Detection of Macular Neovascularization in Eyes Presenting with Macular Edema using OCT Angiography and a Deep Learning Model.
Ophthalmology. Retina
Oct 24, 2024
PURPOSE: To test the diagnostic performance of an artificial intelligence algorithm for detecting and segmenting macular neovascularization (MNV) with OCT and OCT angiography (OCTA) in eyes with macular edema from various diagnoses.
Cross-Sectional Studies
Male
Middle Aged
Deep Learning
Prospective Studies
Female
Aged
Aged, 80 and over
Fluorescein Angiography
Macula Lutea
Retinal Neovascularization
Retinal Vein Occlusion
Visual Acuity
Tomography, Optical Coherence
Fundus Oculi
Macular Edema
Humans
Diabetic Retinopathy
Algorithms
Comparison of Manual vs Artificial Intelligence-Based Muscle MRI Segmentation for Evaluating Disease Progression in Patients With CMT1A.
Neurology
Oct 24, 2024
BACKGROUND AND OBJECTIVES: Intramuscular fat fraction (FF), assessed with quantitative MRI (qMRI), has emerged as one of the few responsive outcome measures in CMT1A patients. The main limitation for its use in future therapeutic trials is the time r...
Deep learning super-resolution reconstruction for fast and high-quality cine cardiovascular magnetic resonance.
European radiology
Oct 23, 2024
OBJECTIVES: To compare standard-resolution balanced steady-state free precession (bSSFP) cine images with cine images acquired at low resolution but reconstructed with a deep learning (DL) super-resolution algorithm.
A Quantitative Comparison Between Human and Artificial Intelligence in the Detection of Focal Cortical Dysplasia.
Investigative radiology
Oct 23, 2024
OBJECTIVES: Artificial intelligence (AI) is thought to improve lesion detection. However, a lack of knowledge about human performance prevents a comparative evaluation of AI and an accurate assessment of its impact on clinical decision-making. The ob...
Multimodal ultrasound deep learning to detect fibrosis in early chronic kidney disease.
Renal failure
Oct 22, 2024
We developed a multimodal ultrasound (US) deep learning (DL) fusion model to automatically classify early fibrosis in patients with chronic kidney disease (CKD). This prospective study included patients with CKD who underwent continuous gray-scale US...
A deep learning-based, real-time image report system for linear EUS.
Gastrointestinal endoscopy
Oct 19, 2024
BACKGROUND AND AIMS: The integrity of image acquisition is critical for biliopancreatic EUS reporting, significantly affecting the quality of EUS examinations and disease-related decision-making. However, the quality of EUS reports varies among endos...
Machine learning models of cerebral oxygenation (rcSO) for brain injury detection in neonates with hypoxic-ischaemic encephalopathy.
The Journal of physiology
Oct 19, 2024
The present study was designed to test the potential utility of regional cerebral oxygen saturation (rcSO) in detecting term infants with brain injury. The study also examined whether quantitative rcSO features are associated with grade of hypoxic is...
The Efficacy of a Food Supplement in the Treatment of Tinnitus with Comorbid Headache: A Statistical and Machine Learning Analysis with a Literature Review.
Audiology & neuro-otology
Oct 18, 2024
INTRODUCTION: Tinnitus, the perception of sound without an external auditory stimulus, affects approximately 10-15% of the population and is often associated with significant comorbidities such as headaches. These conditions can severely impact the q...
Diagnostic performance of single-lead electrocardiograms for arterial hypertension diagnosis: a machine learning approach.
Journal of human hypertension
Oct 18, 2024
Awareness and early identification of hypertension is crucial in reducing the burden of cardiovascular disease (CVD). Artificial intelligence-based analysis of 12-lead electrocardiograms (ECGs) can already detect arrhythmias and hypertension. We perf...
Exploring the potential of artificial intelligence models for triage in the emergency department.
Postgraduate medicine
Oct 17, 2024
OBJECTIVE: To perform a comparative analysis of the three-level triage protocol conducted by triage nurses and emergency medicine doctors with the use of ChatGPT, Gemini, and Pi, which are recognized artificial intelligence (AI) models widely used in...
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