AIMC Topic: Neural Networks, Computer

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Prediction of PM concentration based on a CNN-LSTM neural network algorithm.

PeerJ
Fine particulate matter (PM) is a major air pollutant affecting human survival, development and health. By predicting the spatial distribution concentration of PM, pollutant sources can be better traced, allowing measures to protect human health to b...

Protein ligand binding site prediction using graph transformer neural network.

PloS one
Ligand binding site prediction is a crucial initial step in structure-based drug discovery. Although several methods have been proposed previously, including those using geometry based and machine learning techniques, their accuracy is considered to ...

Common sleep data pipeline for combined data sets.

PloS one
Over the past few years, sleep research has shown impressive performance of deep neural networks in the area of automatic sleep-staging. Recent studies have demonstrated the necessity of combining multiple data sets to obtain sufficiently generalizin...

Iteratively Calibratable Network for Reliable EEG-Based Robotic Arm Control.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Robotic arms are increasingly being utilized in shared workspaces, which necessitates the accurate interpretation of human intentions for both efficiency and safety. Electroencephalogram (EEG) signals, commonly employed to measure brain activity, off...

DEAF-Net: Detail-Enhanced Attention Feature Fusion Network for Retinal Vessel Segmentation.

Journal of imaging informatics in medicine
Retinal vessel segmentation is crucial for the diagnosis of ophthalmic and cardiovascular diseases. However, retinal vessels are densely and irregularly distributed, with many capillaries blending into the background, and exhibit low contrast. Moreov...

The heart sound classification of congenital heart disease by using median EEMD-Hurst and threshold denoising method.

Medical & biological engineering & computing
Heart sound signals are vital for the machine-assisted detection of congenital heart disease. However, the performance of diagnostic results is limited by noise during heart sound acquisition. A limitation of existing noise reduction schemes is that ...

Multi-step framework for glaucoma diagnosis in retinal fundus images using deep learning.

Medical & biological engineering & computing
Glaucoma is one of the most common causes of blindness in the world. Screening glaucoma from retinal fundus images based on deep learning is a common method at present. In the diagnosis of glaucoma based on deep learning, the blood vessels within the...

Automated detection and classification of mandibular fractures on multislice spiral computed tomography using modified convolutional neural networks.

Oral surgery, oral medicine, oral pathology and oral radiology
OBJECTIVE: To evaluate the performance of convolutional neural networks (CNNs) for the automated detection and classification of mandibular fractures on multislice spiral computed tomography (MSCT).

Few-shot learning with representative global prototype.

Neural networks : the official journal of the International Neural Network Society
Few-shot learning is often challenged by low generalization performance due to the model is mostly learned with the base classes only. To mitigate the above issues, a few-shot learning method with representative global prototype is proposed in this p...

Real-time hardware emulation of neural cultures: A comparative study of in vitro, in silico and in duris silico models.

Neural networks : the official journal of the International Neural Network Society
Biological neural networks are well known for their capacity to process information with extremely low power consumption. Fields such as Artificial Intelligence, with high computational costs, are seeking for alternatives inspired in biological syste...