AIMC Topic: Reproducibility of Results
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Grading of diabetic retinopathy using a pre-segmenting deep learning classification model: Validation of an automated algorithm.
Acta ophthalmologica
Oct 19, 2024
PURPOSE: To validate the performance of autonomous diabetic retinopathy (DR) grading by comparing a human grader and a self-developed deep-learning (DL) algorithm with gold-standard evaluation.
Quality-related fault detection for dynamic process based on quality-driven long short-term memory network and autoencoder.
Neural networks : the official journal of the International Neural Network Society
Oct 19, 2024
Fault detection consistently plays a crucial role in industrial dynamic processes as it enables timely prevention of production losses. However, since industrial dynamic processes become increasingly coupled and complex, they introduce uneven dynamic...
Hypergraph contrastive attention networks for hyperedge prediction with negative samples evaluation.
Neural networks : the official journal of the International Neural Network Society
Oct 19, 2024
Hyperedge prediction aims to predict common relations among multiple nodes that will occur in the future or remain undiscovered in the current hypergraph. It is traditionally modeled as a classification task, which performs hypergraph feature learnin...
Development and Validation of an Artificial Intelligence-Assisted Patient Education Material for Ostomy Patients: A Methodological Study.
Journal of advanced nursing
Oct 18, 2024
AIM: To develop and test the validity of an artificial intelligence-assisted patient education material for ostomy patients.
Automated AI-based coronary calcium scoring using retrospective CT data from SCAPIS is accurate and correlates with expert scoring.
European radiology
Oct 18, 2024
OBJECTIVES: Evaluation of the correlation and agreement between AI and semi-automatic evaluations of calcium scoring CT (CSCT) examinations using extensive data from the Swedish CardioPulmonary bio-Image study (SCAPIS).
Machine learning localization to identify the epileptogenic side in mesial temporal lobe epilepsy.
Magnetic resonance imaging
Oct 18, 2024
BACKGROUND: Mesial temporal sclerosis (MTS) is the most common pathology associated with drug-resistant mesial temporal lobe epilepsy (mTLE) in adults. Most atrophic hippocampi can be identified using MRI based on standard epilepsy protocols; however...
Machine learning-based discrimination of benign and malignant breast lesions on US: The contribution of shear-wave elastography.
European journal of radiology
Oct 18, 2024
PURPOSE: To build and validate a combined radiomics and machine learning (ML) approach using B-mode US and SWE images to differentiate benign from malignant solid breast lesions (BLs) and compare its performance with that of an expert radiologist.
Assessment of autostereoscopic perception using artificial intelligence-enhanced face tracking technology.
PloS one
Oct 17, 2024
PURPOSE: Stereopsis, the ability of humans to perceive depth through distinct visual stimuli in each eye, is foundational to autostereoscopic technology in computing. However, ensuring stable head position during assessments has been challenging. Thi...
An evaluation of the performance of stopping rules in AI-aided screening for psychological meta-analytical research.
Research synthesis methods
Oct 16, 2024
Several AI-aided screening tools have emerged to tackle the ever-expanding body of literature. These tools employ active learning, where algorithms sort abstracts based on human feedback. However, researchers using these tools face a crucial dilemma:...
USCT-UNet: Rethinking the Semantic Gap in U-Net Network From U-Shaped Skip Connections With Multichannel Fusion Transformer.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Oct 16, 2024
Medical image segmentation is a crucial component of computer-aided clinical diagnosis, with state-of-the-art models often being variants of U-Net. Despite their success, these models' skip connections introduce an unnecessary semantic gap between th...
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