AIMC Topic: Neural Networks, Computer

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General Chemically Intuitive Atom- and Bond-Level DFT Descriptors for Machine Learning Approaches to Reaction Condition Prediction.

Journal of chemical information and modeling
We demonstrate the usefulness of general atom- and bond-level density functional theory (DFT) descriptors to enhance the performance of neural networks for general reaction condition prediction. We treat condition prediction as a multiclass classific...

Soil moisture mapping in Indian tropical islands with C-band SAR and artificial neural network models.

Environmental monitoring and assessment
This study aims at analyzing the patterns of soil moisture in the South Andaman district using an integrated approach that incorporates Sentinel-1A C-band synthetic aperture radar (SAR) data and other auxiliary data from Sentinel-2A and Landsat 8. A ...

Identifying and predicting EEG microstates with sequence-to-sequence deep learning models for online applications.

Journal of neural engineering
Electroencephalographic (EEG) microstates, as a non-invasive and high-temporal-resolution tool for analyzing time-space features of brain activity, have been validated and applied in various research domains. However, current methods for EEG microsta...

Arrhythmia classification based on multi-input convolutional neural network with attention mechanism.

PloS one
Arrhythmia is a prevalent cardiac disorder that can lead to severe complications such as stroke and cardiac arrest. While deep learning has advanced automated ECG analysis, challenges remain in accurately classifying arrhythmias due to signal variabi...

Degradation-Guided cross-consistent deep unfolding network for video restoration under diverse weathers.

Neural networks : the official journal of the International Neural Network Society
Existing video restoration (VR) methods have made promising progress in improving the quality of videos degraded by adverse weather. However, these approaches only restore videos with one specific type of degradation and ignore the diversity of degra...

New artificial neural network models for risk assessment of skin sensitization using amino acid derivative assay, KeratinoSens™, human cell line activation test and in silico structural alert parameter.

Regulatory toxicology and pharmacology : RTP
In the next-generation risk assessment (NGRA) of skin sensitization, estimating the point of departure (PoD) is crucial. The murine local lymph node assay (LLNA) has been considered the 'gold standard' for evaluating the skin sensitizing potential of...

Low-field NMR-based deep learning for non-destructive quality assessment of frozen model foods.

Food chemistry
Gel model foods with 90 % and 80 % water content were prepared for non-destructive quality testing of samples frozen under gradient temperature conditions. First, the drip loss and textural indices of the frozen samples were measured, and the nucleat...

An anxiety screening framework integrating multimodal data and graph node correlation.

Artificial intelligence in medicine
Anxiety disorders are a significant global health concern, profoundly impacting patients' lives and social functioning while imposing considerable burdens on families and economies. However, current anxiety screening methods face limitations due to c...

Machine learning strategies for multi-label pre-diagnosis of diseases with superficial data.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: General practice (GP) pre-diagnosis, a key task in disease triage, directs patients to suitable departments despite limited data and multi-label classification challenges. To address this issue, a framework with dimensionali...

VAE-GANMDA: A microbe-drug association prediction model integrating variational autoencoders and generative adversarial networks.

Artificial intelligence in medicine
Traditional biological experimental methods typically require weeks or even months of experimentation, and the cost of each experiment can reach hundreds or even thousands of dollars, which is quite expensive and time-consuming. To address this, a mo...