AIMC Topic: Reproducibility of Results

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An Intelligent Channel Estimation Algorithm Based on Extended Model for 5G-V2X.

Big data
Car networking systems based on 5G-V2X (vehicle-to-everything) have high requirements for reliability and low-latency communication to further improve communication performance. In the V2X scenario, this article establishes an extended model (basic e...

COVID-Net USPro: An Explainable Few-Shot Deep Prototypical Network for COVID-19 Screening Using Point-of-Care Ultrasound.

Sensors (Basel, Switzerland)
As the Coronavirus Disease 2019 (COVID-19) continues to impact many aspects of life and the global healthcare systems, the adoption of rapid and effective screening methods to prevent the further spread of the virus and lessen the burden on healthcar...

Automatic grading of patients with a unilateral facial paralysis based on the Sunnybrook Facial Grading System - A deep learning study based on a convolutional neural network.

American journal of otolaryngology
PURPOSE: In order to assess the severity and the progression of a unilateral peripheral facial palsy the Sunnybrook Facial Grading System (SFGS) is a well-established grading system due to its clinical relevance, sensitivity, and robust measuring met...

Image-based estimation of the left ventricular cavity volume using deep learning and Gaussian process with cardio-mechanical applications.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
In this investigation, an image-based method has been developed to estimate the volume of the left ventricular cavity using cardiac magnetic resonance (CMR) imaging data. Deep learning and Gaussian processes have been applied to bring the estimations...

Reliability of respiratory-gated real-time two-dimensional cine incorporating deep learning reconstruction for the assessment of ventricular function in an adult population; a common mistake.

The international journal of cardiovascular imaging
Reliability (repeatability or agreement) is assessed by different statistical tests including Pearson r or Spearman rho which is one of the common mistakes in reliability analysis. Pearson r or Spearman rho correlation coefficient only assesses the l...

Increasing transparency in machine learning through bootstrap simulation and shapely additive explanations.

PloS one
Machine learning methods are widely used within the medical field. However, the reliability and efficacy of these models is difficult to assess, making it difficult for researchers to identify which machine-learning model to apply to their dataset. W...

Deep Learning Approach for MRI in the Classification of Anterior Talofibular Ligament Injuries.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Diagnosing anterior talofibular ligament (ATFL) injuries differs among radiologists. Further assessment of ATFL tears is valuable for clinical decision-making.

Sinogram domain metal artifact correction of CT via deep learning.

Computers in biology and medicine
PURPOSE: Metal artifacts can significantly decrease the quality of computed tomography (CT) images. This occurs as X-rays penetrate implanted metals, causing severe attenuation and resulting in metal artifacts in the CT images. This degradation in im...

Critical Device Reliability Assessment in Healthcare Services.

Journal of healthcare engineering
Medical device reliability is the ability of medical devices to endure functioning and is indispensable to ensure service delivery to patients. Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) technique was employed in May 2...

A comparative study of two automated solutions for cross-sectional skeletal muscle measurement from abdominal computed tomography images.

Medical physics
BACKGROUND: Measurement of cross-sectional muscle area (CSMA) at the mid third lumbar vertebra (L3) level from computed tomography (CT) images is becoming one of the reference methods for sarcopenia diagnosis. However, manual skeletal muscle segmenta...