AIMC Topic: Neural Networks, Computer

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Automated age estimation of young individuals based on 3D knee MRI using deep learning.

International journal of legal medicine
Age estimation is a crucial element of forensic medicine to assess the chronological age of living individuals without or lacking valid legal documentation. Methods used in practice are labor-intensive, subjective, and frequently comprise radiation e...

The emerging role of deep learning in cytology.

Cytopathology : official journal of the British Society for Clinical Cytology
Deep learning (DL) is a component or subset of artificial intelligence. DL has contributed significant change in feature extraction and image classification. Various algorithmic models are used in DL such as a convolutional neural network (CNN), recu...

Finding Distributed Needles in Neural Haystacks.

The Journal of neuroscience : the official journal of the Society for Neuroscience
The human cortex encodes information in complex networks that can be anatomically dispersed and variable in their microstructure across individuals. Using simulations with neural network models, we show that contemporary statistical methods for funct...

Comparative analysis of active contour and convolutional neural network in rapid left-ventricle volume quantification using echocardiographic imaging.

Computer methods and programs in biomedicine
In cardiology, ultrasound is often used to diagnose heart disease associated with myocardial infarction. This study aims to develop robust segmentation techniques for segmenting the left ventricle (LV) in ultrasound images to check myocardium movemen...

A simple Ca-imaging approach to neural network analyses in cultured neurons.

Journal of neuroscience methods
BACKGROUND: Ca-imaging is a powerful tool to measure neuronal dynamics and network activity. To monitor network-level changes in cultured neurons, neuronal activity is often evoked by electrical or optogenetic stimulation and assessed using multi-ele...

InstanceEasyTL: An Improved Transfer-Learning Method for EEG-Based Cross-Subject Fatigue Detection.

Sensors (Basel, Switzerland)
Electroencephalogram (EEG) is an effective indicator for the detection of driver fatigue. Due to the significant differences in EEG signals across subjects, and difficulty in collecting sufficient EEG samples for analysis during driving, detecting fa...

Hardware-Based Hopfield Neuromorphic Computing for Fall Detection.

Sensors (Basel, Switzerland)
With the popularity of smart wearable systems, sensor signal processing poses more challenges to machine learning in embedded scenarios. For example, traditional machine-learning methods for data classification, especially in real time, are computati...

Identification of Alzheimer's disease using a convolutional neural network model based on T1-weighted magnetic resonance imaging.

Scientific reports
The classification of Alzheimer's disease (AD) using deep learning methods has shown promising results, but successful application in clinical settings requires a combination of high accuracy, short processing time, and generalizability to various po...

Comparing feedforward and recurrent neural network architectures with human behavior in artificial grammar learning.

Scientific reports
In recent years artificial neural networks achieved performance close to or better than humans in several domains: tasks that were previously human prerogatives, such as language processing, have witnessed remarkable improvements in state of the art ...

Multimodal fusion with deep neural networks for leveraging CT imaging and electronic health record: a case-study in pulmonary embolism detection.

Scientific reports
Recent advancements in deep learning have led to a resurgence of medical imaging and Electronic Medical Record (EMR) models for a variety of applications, including clinical decision support, automated workflow triage, clinical prediction and more. H...