AIMC Topic: Neural Networks, Computer

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A Novel Event-Driven Spiking Convolutional Neural Network for Electromyography Pattern Recognition.

IEEE transactions on bio-medical engineering
Electromyography (EMG) pattern recognition is an important technology for prosthesis control and human-computer interaction etc. However, the practical application of EMG pattern recognition is hampered by poor accuracy and robustness due to electrod...

Omni-Seg: A Scale-Aware Dynamic Network for Renal Pathological Image Segmentation.

IEEE transactions on bio-medical engineering
Comprehensive semantic segmentation on renal pathological images is challenging due to the heterogeneous scales of the objects. For example, on a whole slide image (WSI), the cross-sectional areas of glomeruli can be 64 times larger than that of the ...

Efficient Generation of Pretraining Samples for Developing a Deep Learning Brain Injury Model via Transfer Learning.

Annals of biomedical engineering
The large amount of training samples required to develop a deep learning brain injury model demands enormous computational resources. Here, we study how a transformer neural network (TNN) of high accuracy can be used to efficiently generate pretraini...

Deep Learning Ultrasound Computed Tomography Under Sparse Sampling.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Ultrasound computed tomography (USCT) is a fast-emerging imaging modality that is expected to help detect and characterize breast tumors by quantifying the distribution of the speed of sound (SOS) and acoustic attenuation in breast tissue. High-quali...

Ultrasound Frame-to-Volume Registration via Deep Learning for Interventional Guidance.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Fusing intraoperative 2-D ultrasound (US) frames with preoperative 3-D magnetic resonance (MR) images for guiding interventions has become the clinical gold standard in image-guided prostate cancer biopsy. However, developing an automatic image regis...

Deep learning algorithm for visual quality assessment of the spirograms.

Physiological measurement
. The quality of spirometry manoeuvres is crucial for correctly interpreting the values of spirometry parameters. A fundamental guideline for proper quality assessment is the American Thoracic Society and European Respiratory Society (ATS/ERS) Standa...

Prediction of municipal solid waste generation and analysis of dominant variables in rapidly developing cities based on machine learning - a case study of China.

Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA
Prediction of municipal solid waste (MSW) generation plays an essential role in effective waste management. The main objectives of this study were to develop models for accurate prediction of MSW generation (MSWG) and analyze the influence of dominan...

Shortening image registration time using a deep neural network for patient positional verification in radiotherapy.

Physical and engineering sciences in medicine
We sought to accelerate 2D/3D image registration computation time using image synthesis with a deep neural network (DNN) to generate digitally reconstructed radiographic (DRR) images from X-ray flat panel detector (FPD) images. And we explored the fe...

Criticality and clinical department prediction of ED patients using machine learning based on heterogeneous medical data.

Computers in biology and medicine
PROBLEM: Emergency triage faces multiple challenges, including limited medical resources and inadequate manual triage nurses, which cause incorrect triage, overcrowding in the emergency department (ED), and long patient waiting time.

DeepGRID: Deep Learning Using GRID Descriptors for BBB Prediction.

Journal of chemical information and modeling
Deep Learning approaches are able to automatically extract relevant features from the input data and capture nonlinear relationships between the input and output. In this work, we present the GRID-derived AI (GrAId) descriptors, a simple modification...