AIMC Topic: Reproducibility of Results
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Novel use of deep neural networks on photographic identification of epaulette sharks (Hemiscyllium ocellatum) across life stages.
Journal of fish biology
Aug 10, 2024
Photographic identification (photo ID) is an established method that is used to count animals and track individuals' movements. This method performs well with some species of elasmobranchs (i.e., sharks, skates, and rays) where individuals have disti...
Automated Method for Growing Rod Length Measurement on Ultrasound Images in Children With Early Onset Scoliosis.
Ultrasound in medicine & biology
Aug 10, 2024
OBJECTIVE: To develop and validate machine learning algorithms to automatically extract the rod length of the magnetically controlled growing rod from ultrasound images (US) in a pilot study.
Assessment of left ventricular wall thickness and dimension: accuracy of a deep learning model with prediction uncertainty.
The international journal of cardiovascular imaging
Aug 10, 2024
Left ventricular (LV) geometric patterns aid clinicians in the diagnosis and prognostication of various cardiomyopathies. The aim of this study is to assess the accuracy and reproducibility of LV dimensions and wall thickness using deep learning (DL)...
Artificial intelligence-based classification of cardiac autonomic neuropathy from retinal fundus images in patients with diabetes: The Silesia Diabetes Heart Study.
Cardiovascular diabetology
Aug 10, 2024
BACKGROUND: Cardiac autonomic neuropathy (CAN) in diabetes mellitus (DM) is independently associated with cardiovascular (CV) events and CV death. Diagnosis of this complication of DM is time-consuming and not routinely performed in the clinical prac...
Impact of training data composition on the generalizability of convolutional neural network aortic cross-section segmentation in four-dimensional magnetic resonance flow imaging.
Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
Aug 8, 2024
BACKGROUND: Four-dimensional cardiovascular magnetic resonance flow imaging (4D flow CMR) plays an important role in assessing cardiovascular diseases. However, the manual or semi-automatic segmentation of aortic vessel boundaries in 4D flow data int...
Perfusion Imaging
Bicuspid Aortic Valve Disease
Aortic Valve
Middle Aged
Aged
Datasets as Topic
Humans
Predictive Value of Tests
Young Adult
Blood Flow Velocity
Case-Control Studies
Neural Networks, Computer
Regional Blood Flow
Adult
Aorta
Image Interpretation, Computer-Assisted
Hemodynamics
Female
Male
Reproducibility of Results
Deep Learning
DCE-Qnet: deep network quantification of dynamic contrast enhanced (DCE) MRI.
Magma (New York, N.Y.)
Aug 8, 2024
INTRODUCTION: Quantification of dynamic contrast-enhanced (DCE)-MRI has the potential to provide valuable clinical information, but robust pharmacokinetic modeling remains a challenge for clinical adoption.
Improving ED admissions forecasting by using generative AI: An approach based on DGAN.
Computer methods and programs in biomedicine
Aug 8, 2024
BACKGROUND AND OBJECTIVE: Generative Deep Learning has emerged in recent years as a significant player in the Artificial Intelligence field. Synthesizing new data while maintaining the features of reality has revolutionized the field of Deep Learning...
Diabetic retinopathy screening with confocal fundus camera and artificial intelligence - assisted grading.
European journal of ophthalmology
Aug 7, 2024
PURPOSE: Screening for diabetic retinopathy (DR) by ophthalmologists is costly and labour-intensive. Artificial Intelligence (AI) for automated DR detection could be a clinically and economically alternative. We assessed the performance of a confocal...
Automated remote sleep monitoring needs uncertainty quantification.
Journal of sleep research
Aug 7, 2024
Wearable electroencephalography devices emerge as a cost-effective and ergonomic alternative to gold-standard polysomnography, paving the way for better health monitoring and sleep disorder screening. Machine learning allows to automate sleep stage c...
Optimization of the automated Sunnybrook Facial Grading System - Improving the reliability of a deep learning network with facial landmarks.
European annals of otorhinolaryngology, head and neck diseases
Aug 7, 2024
OBJECTIVE: The Sunnybrook Facial Grading System (SFGS) is a well-established grading system to assess the severity and progression of a unilateral facial palsy. The automation of the SFGS makes the SFGS more accessible for researchers, students, clin...
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