AIMC Topic: Neural Networks, Computer

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Inter-crystal scattering event identification using a novel silicon photomultiplier signal multiplexing method.

Physics in medicine and biology
Identifying the inter-crystal scatter (ICS) events and recovering the first interaction position enables the accurate determination of the line-of-response in positron emission tomography (PET). However, conventional silicon photomultiplier (SiPM) si...

Classification of breast tumors by using a novel approach based on deep learning methods and feature selection.

Breast cancer research and treatment
PURPOSE: Cancer is one of the most insidious diseases that the most important factor in overcoming the cancer is early diagnosis and detection. The histo-pathological images are used to determine whether the tissue is cancerous and the type of cancer...

Using artificial intelligence models to evaluate envisaged points initially: A pilot study.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
The morphology of the finger bones in hand-wrist radiographs (HWRs) can be considered as a radiological skeletal maturity indicator, along with the other indicators. This study aims to validate the anatomical landmarks envisaged to be used for classi...

Automatic multi-label temporal bone computed tomography segmentation with deep learning.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Manually segmenting temporal bone computed tomography (CT) images is difficult. Despite accurate automatic segmentation in previous studies using deep learning, they did not consider clinical differences, such as variations in CT scanners...

LoyalDE: Improving the performance of Graph Neural Networks with loyal node discovery and emphasis.

Neural networks : the official journal of the International Neural Network Society
Recent years have witnessed an increasing focus on graph-based semi-supervised learning with Graph Neural Networks (GNNs). Despite existing GNNs having achieved remarkable accuracy, research on the quality of graph supervision information has inadver...

Continual learning with invertible generative models.

Neural networks : the official journal of the International Neural Network Society
Catastrophic forgetting (CF) happens whenever a neural network overwrites past knowledge while being trained on new tasks. Common techniques to handle CF include regularization of the weights (using, e.g., their importance on past tasks), and rehears...

Estimating Uncertainty in Neural Networks for Cardiac MRI Segmentation: A Benchmark Study.

IEEE transactions on bio-medical engineering
OBJECTIVE: Convolutional neural networks (CNNs) have demonstrated promise in automated cardiac magnetic resonance image segmentation. However, when using CNNs in a large real-world dataset, it is important to quantify segmentation uncertainty and ide...

Spatiotemporal Compliance Control for a Wearable Lower Limb Rehabilitation Robot.

IEEE transactions on bio-medical engineering
Compliance control is crucial for physical human-robot interaction, which can enhance the safety and comfort of robot-assisted rehabilitation. In this study, we designed a spatiotemporal compliance control strategy for a new self-designed wearable lo...

Performance of a Convolutional Neural Network Derived From PPG Signal in Classifying Sleep Stages.

IEEE transactions on bio-medical engineering
Automatic sleep stage classification is vital for evaluating the quality of sleep. Conventionally, sleep is monitored using multiple physiological sensors that are uncomfortable for long-term monitoring and require expert intervention. In this study,...

Using Machine Learning Algorithms to Pool Data from Meta-Analysis for the Prediction of Countermovement Jump Improvement.

International journal of environmental research and public health
To solve the research-practice gap and take one step forward toward using big data with real-world evidence, the present study aims to adopt a novel method using machine learning to pool findings from meta-analyses and predict the change of countermo...