AIMC Topic: Deep Learning

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Modeling the response of ecological service value to land use change through deep learning simulation in Lanzhou, China.

The Science of the total environment
Land use (LU) changes caused by urbanization, climate, and anthropogenic activities alter the supply of ecosystem services (ES), which affects the ecological service value (ESV) of a given region. Existing LU simulation models extract neighborhood ef...

Inter-laboratory automation of the in vitro micronucleus assay using imaging flow cytometry and deep learning.

Archives of toxicology
The in vitro micronucleus assay is a globally significant method for DNA damage quantification used for regulatory compound safety testing in addition to inter-individual monitoring of environmental, lifestyle and occupational factors. However, it re...

Deep learning algorithms for automatic detection of pterygium using anterior segment photographs from slit-lamp and hand-held cameras.

The British journal of ophthalmology
BACKGROUND/AIMS: To evaluate the performances of deep learning (DL) algorithms for detection of presence and extent pterygium, based on colour anterior segment photographs (ASPs) taken from slit-lamp and hand-held cameras.

Deep-learning based super-resolution for 3D isotropic coronary MR angiography in less than a minute.

Magnetic resonance in medicine
PURPOSE: To develop and evaluate a novel and generalizable super-resolution (SR) deep-learning framework for motion-compensated isotropic 3D coronary MR angiography (CMRA), which allows free-breathing acquisitions in less than a minute.

Automatic left ventricle volume calculation with explainability through a deep learning weak-supervision methodology.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Magnetic resonance imaging is the most reliable imaging technique to assess the heart. More specifically there is great importance in the analysis of the left ventricle, as the main pathologies directly affect this region. I...

Understand the impact of traffic states on crash risk in the vicinities of Type A weaving segments: A deep learning approach.

Accident; analysis and prevention
The primary objective of this study was to evaluate the impacts of traffic states on crash risk in the vicinities of Type A weaving segments. A deep convolutional embedded clustering (DCEC) was developed to classify traffic flow into nine states. The...

Artificial Intelligence-Assisted Early Detection of Retinitis Pigmentosa - the Most Common Inherited Retinal Degeneration.

Journal of digital imaging
The purpose of this study was to detect the presence of retinitis pigmentosa (RP) based on color fundus photographs using a deep learning model. A total of 1670 color fundus photographs from the Taiwan inherited retinal degeneration project and Natio...

Physical Activity Recognition Based on a Parallel Approach for an Ensemble of Machine Learning and Deep Learning Classifiers.

Sensors (Basel, Switzerland)
Human activity recognition (HAR) by wearable sensor devices embedded in the Internet of things (IOT) can play a significant role in remote health monitoring and emergency notification to provide healthcare of higher standards. The purpose of this stu...

Driving Behaviour Analysis Using Machine and Deep Learning Methods for Continuous Streams of Vehicular Data.

Sensors (Basel, Switzerland)
In the last few decades, vehicles are equipped with a plethora of sensors which can provide useful measurements and diagnostics for both the vehicle's condition as well as the driver's behaviour. Furthermore, the rapid increase for transportation nee...

A clinical deep learning framework for continually learning from cardiac signals across diseases, time, modalities, and institutions.

Nature communications
Deep learning algorithms trained on instances that violate the assumption of being independent and identically distributed (i.i.d.) are known to experience destructive interference, a phenomenon characterized by a degradation in performance. Such a v...