AIMC Topic: Neural Networks, Computer

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Diagnostic outcomes of esophageal cancer by artificial intelligence using convolutional neural networks.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: The prognosis of esophageal cancer is relatively poor. Patients are usually diagnosed at an advanced stage when it is often too late for effective treatment. Recently, artificial intelligence (AI) using deep learning has made rem...

Estimating regional effects of climate change and altered land use on biosphere carbon fluxes using distributed time delay neural networks with Bayesian regularized learning.

Neural networks : the official journal of the International Neural Network Society
The ability to accurately predict changes of the carbon and energy balance on a regional scale is of great importance for assessing the effect of land use changes on carbon sequestration under future climate conditions. Here, a suite of land cover-sp...

Transfer learning for classification of cardiovascular tissues in histological images.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Automatic classification of healthy tissues and organs based on histology images is an open problem, mainly due to the lack of automated tools. Solutions in this regard have potential in educational medicine and medical prac...

Predicting postoperative facial swelling following impacted mandibular third molars extraction by using artificial neural networks evaluation.

Scientific reports
Patients' postoperative facial swelling following third molars extraction may have both biological impacts and social impacts. The purpose of this study was to evaluate the accuracy of artificial neural networks in the prediction of the postoperative...

Personalized Exposure Control Using Adaptive Metering and Reinforcement Learning.

IEEE transactions on visualization and computer graphics
We propose a reinforcement learning approach for real-time exposure control of a mobile camera that is personalizable. Our approach is based on Markov Decision Process (MDP). In the camera viewfinder or live preview mode, given the current frame, our...

A convolutional route to abbreviation disambiguation in clinical text.

Journal of biomedical informatics
OBJECTIVE: Abbreviations sense disambiguation is a special case of word sense disambiguation. Machine learning methods based on neural networks showed promising results for word sense disambiguation (Festag and Spreckelsen, 2017) [1] and, here we ass...

An Intelligent Model for Blood Vessel Segmentation in Diagnosing DR Using CNN.

Journal of medical systems
Diabetic retinopathy (DR) is an eye disease, which affects the people who are all having the diabetes for more than 10 years. The ophthalmologist identifies when the dilated eye exam causes severe in any one of the following deviations in the retina:...

Convolutional Neural Network With Shape Prior Applied to Cardiac MRI Segmentation.

IEEE journal of biomedical and health informatics
In this paper, we present a novel convolutional neural network architecture to segment images from a series of short-axis cardiac magnetic resonance slices (CMRI). The proposed model is an extension of the U-net that embeds a cardiac shape prior and ...