AIMC Topic: Reproducibility of Results

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Deep Learning-Based Sentiment Analysis of COVID-19 Vaccination Responses from Twitter Data.

Computational and mathematical methods in medicine
The COVID-19 pandemic has had a devastating effect on many people, creating severe anxiety, fear, and complicated feelings or emotions. After the initiation of vaccinations against coronavirus, people's feelings have become more diverse and complex. ...

Forecasting of Patient-Specific Kidney Transplant Function With a Sequence-to-Sequence Deep Learning Model.

JAMA network open
IMPORTANCE: Like other clinical biomarkers, trajectories of estimated glomerular filtration rate (eGFR) after kidney transplant are characterized by intra-individual variability. These fluctuations hamper the distinction between alarming graft functi...

Fully automatic segmentation of the mandible based on convolutional neural networks (CNNs).

Orthodontics & craniofacial research
OBJECTIVES: To evaluate the accuracy of automatic deep learning-based method for fully automatic segmentation of the mandible from CBCTs.

Artificial intelligence (AI)-assisted exome reanalysis greatly aids in the identification of new positive cases and reduces analysis time in a clinical diagnostic laboratory.

Genetics in medicine : official journal of the American College of Medical Genetics
PURPOSE: Artificial intelligence (AI) and variant prioritization tools for genomic variant analysis are being rapidly developed for use in clinical diagnostic testing. However, their clinical utility and reliability are currently limited. Therefore, ...

Probabilistic Deep Learning to Quantify Uncertainty in Air Quality Forecasting.

Sensors (Basel, Switzerland)
Data-driven forecasts of air quality have recently achieved more accurate short-term predictions. However, despite their success, most of the current data-driven solutions lack proper quantifications of model uncertainty that communicate how much to ...

Artificial intelligence X-ray measurement technology of anatomical parameters related to lumbosacral stability.

European journal of radiology
PURPOSE: To develop a deep learning-based model for measuring automatic lumbosacral anatomical parameters from lateral lumbar radiographs and compare its performance to that of attending-level radiologists.

Detection and Classification System for Rail Surface Defects Based on Eddy Current.

Sensors (Basel, Switzerland)
The prospect of growth of a railway system impacts both the network size and its occupation. Due to the overloaded infrastructure, it is necessary to increase reliability by adopting fast maintenance services to reach economic and security conditions...

Direct left-ventricular global longitudinal strain (GLS) computation with a fully convolutional network.

Journal of biomechanics
This study's purpose was to develop a direct MRI-based, deep-learning semantic segmentation approach for computing global longitudinal strain (GLS), a known metric for detecting left-ventricular (LV) cardiotoxicity in breast cancer. Displacement Enco...

Fuzzy Logic in Aircraft Onboard Systems Reliability Evaluation-A New Approach.

Sensors (Basel, Switzerland)
This paper is a continuation of research into the possibility of using fuzzy logic to assess the reliability of a selected airborne system. The research objectives include an analysis of statistical data, a reliability analysis in the classical appro...

Extending Camera's Capabilities in Low Light Conditions Based on LIP Enhancement Coupled with CNN Denoising.

Sensors (Basel, Switzerland)
Using a sensor in variable lighting conditions, especially very low-light conditions, requires the application of image enhancement followed by denoising to retrieve correct information. The limits of such a process are explored in the present paper,...