AIMC Topic: Deep Learning

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Integrating artificial intelligence, machine learning, and deep learning approaches into remediation of contaminated sites: A review.

Chemosphere
The growing number of contaminated sites across the world pose a considerable threat to the environment and human health. Remediating such sites is a cumbersome process with the complexity originating from the need for extensive sampling and testing ...

Amharic political sentiment analysis using deep learning approaches.

Scientific reports
This study delves into the realm of sentiment analysis in the Amharic language, focusing on political sentences extracted from social media platforms in Ethiopia. The research employs deep learning techniques, including Convolutional Neural Networks ...

A novel bidirectional LSTM deep learning approach for COVID-19 forecasting.

Scientific reports
COVID-19 has resulted in significant morbidity and mortality globally. We develop a model that uses data from thirty days before a fixed time point to forecast the daily number of new COVID-19 cases fourteen days later in the early stages of the pand...

Deep-learning-based cross-modality translation from Stokes image to bright-field contrast.

Journal of biomedical optics
SIGNIFICANCE: Mueller matrix (MM) microscopy has proven to be a powerful tool for probing microstructural characteristics of biological samples down to subwavelength scale. However, in clinical practice, doctors usually rely on bright-field microscop...

Predicting of diabetic retinopathy development stages of fundus images using deep learning based on combined features.

PloS one
The number of diabetic retinopathy (DR) patients is increasing every year, and this causes a public health problem. Therefore, regular diagnosis of diabetes patients is necessary to avoid the progression of DR stages to advanced stages that lead to b...

Development of a novel combined nomogram model integrating deep learning radiomics to diagnose IgA nephropathy clinically.

Renal failure
This study aimed to develop and validate a combined nomogram model based on superb microvascular imaging (SMI)-based deep learning (DL), radiomics characteristics, and clinical factors for noninvasive differentiation between immunoglobulin A nephropa...

Accelerated Cine Cardiac MRI Using Deep Learning-Based Reconstruction: A Systematic Evaluation.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Breath-holding (BH) for cine balanced steady state free precession (bSSFP) imaging is challenging for patients with impaired BH capacity. Deep learning-based reconstruction (DLR) of undersampled k-space promises to shorten BHs while prese...