AIMC Topic: Algorithms

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AQI time series prediction based on a hybrid data decomposition and echo state networks.

Environmental science and pollution research international
A hybrid AQI time series prediction model is proposed based on EWT-SE-VMD secondary decomposition, ICA (imperialist competitive algorithm) feature selection, and ESN (echo state network) neural network. Firstly, EWT (empirical wavelet transform) and ...

AweGNN: Auto-parametrized weighted element-specific graph neural networks for molecules.

Computers in biology and medicine
While automated feature extraction has had tremendous success in many deep learning algorithms for image analysis and natural language processing, it does not work well for data involving complex internal structures, such as molecules. Data represent...

[Machine learning and suicide prevention: is an algorithm the solution?].

Nederlands tijdschrift voor geneeskunde
Suicide is inherently difficult to predict. Epidemiological research identified many general risk factors such as a depression, but these predictors have limited predictive power. Machine learning offers a set of tools that can combine hundreds of pr...

EMDS-5: Environmental Microorganism image dataset Fifth Version for multiple image analysis tasks.

PloS one
Environmental Microorganism Data Set Fifth Version (EMDS-5) is a microscopic image dataset including original Environmental Microorganism (EM) images and two sets of Ground Truth (GT) images. The GT image sets include a single-object GT image set and...

Detection of k-complexes in EEG signals using a multi-domain feature extraction coupled with a least square support vector machine classifier.

Neuroscience research
Sleep scoring is one of the primary tasks for the classification of sleep stages using electroencephalogram (EEG) signals. It is one of the most important diagnostic methods in sleep research and must be carried out with a high degree of accuracy bec...

H synchronization of delayed neural networks via event-triggered dynamic output control.

Neural networks : the official journal of the International Neural Network Society
This paper investigates H exponential synchronization (ES) of neural networks (NNs) with delay by designing an event-triggered dynamic output feedback controller (ETDOFC). The ETDOFC is flexible in practice since it is applicable to both full order a...

Deep learning image reconstruction for pancreatic low-dose computed tomography: comparison with hybrid iterative reconstruction.

Abdominal radiology (New York)
PURPOSE: To evaluate image quality, image noise, and conspicuity of pancreatic ductal adenocarcinoma (PDAC) in pancreatic low-dose computed tomography (LDCT) reconstructed using deep learning image reconstruction (DLIR) and compare with those of imag...

Rice leaf diseases prediction using deep neural networks with transfer learning.

Environmental research
Rice (Oryza sativa) is a principal cereal crop in the world. It is consumed by greater than half of the world's population as a staple food for energy source. The yield production quantity and quality of the rice grain is affecting by abiotic and bio...

Semi-automated weak annotation for deep neural network skin thickness measurement.

Ultrasonic imaging
Correctly calculating skin stiffness with ultrasound shear wave elastography techniques requires an accurate measurement of skin thickness. We developed and compared two algorithms, a thresholding method and a deep learning method, to measure skin th...

Eliminating Indefiniteness of Clinical Spectrum for Better Screening COVID-19.

IEEE journal of biomedical and health informatics
The coronavirus disease 2019 (COVID-19) has swept all over the world. Due to the limited detection facilities, especially in developing countries, a large number of suspected cases can only receive common clinical diagnosis rather than more effective...