AIMC Topic: Deep Learning

Clear Filters Showing 15381 to 15390 of 28423 articles

External COVID-19 Deep Learning Model Validation on ACR AI-LAB: It's a Brave New World.

Journal of the American College of Radiology : JACR
PURPOSE: Deploying external artificial intelligence (AI) models locally can be logistically challenging. We aimed to use the ACR AI-LAB software platform for local testing of a chest radiograph (CXR) algorithm for COVID-19 lung disease severity asses...

Deep learning for automatic diagnosis of gastric dysplasia using whole-slide histopathology images in endoscopic specimens.

Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association
BACKGROUND: Distinguishing gastric epithelial regeneration change from dysplasia and histopathological diagnosis of dysplasia is subject to interobserver disagreement in endoscopic specimens. In this study, we developed a method to distinguish gastri...

Understanding what patients think about hospitals: A deep learning approach for detecting emotions in patient opinions.

Artificial intelligence in medicine
INTRODUCTION: Most hospital assessment systems are based on the study of objective statistical variables as well as patient opinions on their experiences with respect to the services offered by each hospital. Nevertheless, studies have indicated that...

COVID-CCD-Net: COVID-19 and colon cancer diagnosis system with optimized CNN hyperparameters using gradient-based optimizer.

Medical & biological engineering & computing
Coronavirus disease-2019 (COVID-19) is a new types of coronavirus which have turned into a pandemic within a short time. Reverse transcription-polymerase chain reaction (RT-PCR) test is used for the diagnosis of COVID-19 in national healthcare center...

A hybrid resampling algorithms SMOTE and ENN based deep learning models for identification of Marburg virus inhibitors.

Future medicinal chemistry
Marburg virus (MARV) is a sporadic outbreak of a zoonotic disease that causes lethal hemorrhagic fever in humans. We propose a deep learning model with resampling techniques and predict the inhibitory activity of MARV from unknown compounds in the v...

A note on factor normalization for deep neural network models.

Scientific reports
Deep neural network (DNN) models often involve high-dimensional features. In most cases, these high-dimensional features can be decomposed into two parts: a low-dimensional factor and residual features with much-reduced variability and inter-feature ...

A deep learning-based hybrid model of global terrestrial evaporation.

Nature communications
Terrestrial evaporation (E) is a key climatic variable that is controlled by a plethora of environmental factors. The constraints that modulate the evaporation from plant leaves (or transpiration, E) are particularly complex, yet are often assumed to...

Accuracy of advanced deep learning with tensorflow and keras for classifying teeth developmental stages in digital panoramic imaging.

BMC medical imaging
BACKGROUND: This study aims to propose the combinations of image processing and machine learning model to segment the maturity development of the mandibular premolars using a Keras-based deep learning convolutional neural networks (DCNN) model.

Machine learning models outperform deep learning models, provide interpretation and facilitate feature selection for soybean trait prediction.

BMC plant biology
Recent growth in crop genomic and trait data have opened opportunities for the application of novel approaches to accelerate crop improvement. Machine learning and deep learning are at the forefront of prediction-based data analysis. However, few app...

Deep learning for robust and flexible tracking in behavioral studies for C. elegans.

PLoS computational biology
Robust and accurate behavioral tracking is essential for ethological studies. Common methods for tracking and extracting behavior rely on user adjusted heuristics that can significantly vary across different individuals, environments, and experimenta...