AIMC Topic: Deep Learning

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Evaluation of a deep learning system for automatic detection of proximal surface dental caries on bitewing radiographs.

Oral surgery, oral medicine, oral pathology and oral radiology
OBJECTIVE: This study aimed to evaluate a deep learning (DL) system using convolutional neural networks (CNNs) for automatic detection of caries on bitewing radiographs.

Validation of a deep learning segmentation algorithm to quantify the skeletal muscle index and sarcopenia in metastatic renal carcinoma.

European radiology
OBJECTIVES: To validate a deep learning (DL) algorithm for measurement of skeletal muscular index (SMI) and prediction of overall survival in oncology populations.

Automatic Deep-Learning Segmentation of Epicardial Adipose Tissue from Low-Dose Chest CT and Prognosis Impact on COVID-19.

Cells
Background: To develop a deep-learning (DL) pipeline that allowed an automated segmentation of epicardial adipose tissue (EAT) from low-dose computed tomography (LDCT) and investigate the link between EAT and COVID-19 clinical outcomes. Methods: This...

Using deep learning to predict human decisions and using cognitive models to explain deep learning models.

Scientific reports
Deep neural networks (DNNs) models have the potential to provide new insights in the study of cognitive processes, such as human decision making, due to their high capacity and data-driven design. While these models may be able to go beyond theory-dr...

Evaluation and Monitoring of Endometrial Cancer Based on Magnetic Resonance Imaging Features of Deep Learning.

Contrast media & molecular imaging
This study was aimed to compare and analyze the magnetic resonance imaging (MRI) manifestations and surgical pathological results of endometrial cancer (EC) and to explore the clinical research of MRI in the diagnosis and staging of EC. . 80 patients...

Contemporary Urban Space Philosophy in China Using Lightweight Deep Learning Model-Under Ecological Ethics.

Computational intelligence and neuroscience
It aims to improve the construction of ecological civilization and promote the common development of urban and ecology. Firstly, contemporary ecological ethics is explored, and its principles and characteristics are summarized. Then, the technique of...

Cross-Domain Traffic Scene Understanding by Integrating Deep Learning and Topic Model.

Computational intelligence and neuroscience
Understanding cross-domain traffic scenarios from multicamera surveillance network is important for environmental perception. Most of existing methods select the source domain which is most similar to the target domain by comparing entire domains for...

Dense, deep learning-based intracranial aneurysm detection on TOF MRI using two-stage regularized U-Net.

Journal of neuroradiology = Journal de neuroradiologie
BACKGROUND AND PURPOSE: The prevalence of unruptured intracranial aneurysms in the general population is high and aneurysms are usually asymptomatic. Their diagnosis is often fortuitous on MRI and might be difficult and time consuming for the radiolo...

Fully automated deep learning powered calcium scoring in patients undergoing myocardial perfusion imaging.

Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
BACKGROUND: To assess the accuracy of fully automated deep learning (DL) based coronary artery calcium scoring (CACS) from non-contrast computed tomography (CT) as acquired for attenuation correction (AC) of cardiac single-photon-emission computed to...

Deep Learning Forecasts the Occurrence of Sleep Apnea from Single-Lead ECG.

Cardiovascular engineering and technology
OBJECTIVES: Sleep apnea is the most common sleep disorder that leads to serious health complications if not treated early. Forecasting apnea occurrence ahead in time provides the opportunity to take appropriate actions to control and manage it.