AIMC Topic: Reproducibility of Results

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Deep learning prediction of error and skill in robotic prostatectomy suturing.

Surgical endoscopy
BACKGROUND: Manual objective assessment of skill and errors in minimally invasive surgery have been validated with correlation to surgical expertise and patient outcomes. However, assessment and error annotation can be subjective and are time-consumi...

AI-based open-source software for cephalometric analysis from limited FOV radiographs.

Journal of dentistry
BACKGROUND: Artificial Intelligence (AI) in dental diagnostics is evolving, offering innovative approaches for conducting cephalometric analysis with less manual input and overcoming the limitations of traditional imaging methods. To enhance the diag...

Grading of diabetic retinopathy using a pre-segmenting deep learning classification model: Validation of an automated algorithm.

Acta ophthalmologica
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
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
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...

Automated AI-based coronary calcium scoring using retrospective CT data from SCAPIS is accurate and correlates with expert scoring.

European radiology
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
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
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
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...