AIMC Topic: Deep Learning

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Road Traffic Forecast Based on Meteorological Information through Deep Learning Methods.

Sensors (Basel, Switzerland)
Forecasting road flow has strong importance for both allowing authorities to guarantee safety conditions and traffic efficiency, as well as for road users to be able to plan their trips according to space and road occupation. In a summer resort, such...

Editorial of Special Issue "Deep Learning and Machine Learning in Bioinformatics".

International journal of molecular sciences
In recent years, deep learning has emerged as a highly active research field, achieving great success in various machine learning areas, including image processing, speech recognition, and natural language processing, and now rapidly becoming a domin...

A deep learning model identifies emphasis on hard work as an important predictor of income inequality.

Scientific reports
High levels of income inequality can persist in society only if people accept the inequality as justified. To identify psychological predictors of people's tendency to justify inequality, we retrained a pre-existing deep learning model to predict the...

Fully Automatic Knee Joint Segmentation and Quantitative Analysis for Osteoarthritis from Magnetic Resonance (MR) Images Using a Deep Learning Model.

Medical science monitor : international medical journal of experimental and clinical research
BACKGROUND We aimed to develop and evaluate a deep learning-based method for fully automatic segmentation of knee joint MR imaging and quantitative computation of knee osteoarthritis (OA)-related imaging biomarkers. MATERIAL AND METHODS This retrospe...

Transformer-Based Deep-Learning Algorithm for Discriminating Demyelinating Diseases of the Central Nervous System With Neuroimaging.

Frontiers in immunology
BACKGROUND: Differential diagnosis of demyelinating diseases of the central nervous system is a challenging task that is prone to errors and inconsistent reading, requiring expertise and additional examination approaches. Advancements in deep-learnin...

Automatic segmentation of multitype retinal fluid from optical coherence tomography images using semisupervised deep learning network.

The British journal of ophthalmology
BACKGROUND/AIMS: To develop and validate a deep learning model for automated segmentation of multitype retinal fluid using optical coherence tomography (OCT) images.

A deep learning network based on multi-scale and attention for the diagnosis of chronic atrophic gastritis.

Zeitschrift fur Gastroenterologie
BACKGROUND AND STUDY AIM: Chronic atrophic gastritis plays an important role in the process of gastric cancer. Deep learning is gradually introduced in the medical field, and how to better apply a convolutional neural network (CNN) to the diagnosis o...

EPI phase error correction with deep learning (PEC-DL) at 7 T.

Magnetic resonance in medicine
PURPOSE: The phase mismatch between odd and even echoes in EPI causes Nyquist ghost artifacts. Existing ghost correction methods often suffer from severe residual artifacts and are ineffective with k-space undersampling data. This study proposed a de...

A Novel Deep Learning-Based Cooperative Communication Channel Model for Wireless Underground Sensor Networks.

Sensors (Basel, Switzerland)
Wireless Underground Sensor Networks (WUSNs) have been showing prospective supervising application domains in the underground region of the earth through sensing, computation, and communication. This paper presents a novel Deep Learning (DL)-based Co...

CancerNet: a unified deep learning network for pan-cancer diagnostics.

BMC bioinformatics
BACKGROUND: Despite remarkable advances in cancer research, cancer remains one of the leading causes of death worldwide. Early detection of cancer and localization of the tissue of its origin are key to effective treatment. Here, we leverage technolo...