AIMC Topic: Algorithms

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FPWT: Filter pruning via wavelet transform for CNNs.

Neural networks : the official journal of the International Neural Network Society
The enormous data and computational resources required by Convolutional Neural Networks (CNNs) hinder the practical application on mobile devices. To solve this restrictive problem, filter pruning has become one of the practical approaches. At presen...

DGSD: Dynamical graph self-distillation for EEG-based auditory spatial attention detection.

Neural networks : the official journal of the International Neural Network Society
Auditory Attention Detection (AAD) aims to detect the target speaker from brain signals in a multi-speaker environment. Although EEG-based AAD methods have shown promising results in recent years, current approaches primarily rely on traditional conv...

An unrolled neural network for accelerated dynamic MRI based on second-order half-quadratic splitting model.

Magnetic resonance imaging
The reconstruction of dynamic magnetic resonance images from incomplete k-space data has sparked significant research interest due to its potential to reduce scan time. However, traditional iterative optimization algorithms fail to faithfully reconst...

Machine Learning Methods to Estimate Individualized Treatment Effects for Use in Health Technology Assessment.

Medical decision making : an international journal of the Society for Medical Decision Making
BACKGROUND: Recent developments in causal inference and machine learning (ML) allow for the estimation of individualized treatment effects (ITEs), which reveal whether treatment effectiveness varies according to patients' observed covariates. ITEs ca...

Diagnostic Performance of Machine Learning-based Models in Neonatal Sepsis: A Systematic Review.

The Pediatric infectious disease journal
BACKGROUND: Timely diagnosis of neonatal sepsis is challenging. We aimed to systematically evaluate the diagnostic performance of sophisticated machine learning (ML) techniques for the prediction of neonatal sepsis.

Model-based federated learning for accurate MR image reconstruction from undersampled k-space data.

Computers in biology and medicine
Deep learning-based methods have achieved encouraging performances in the field of Magnetic Resonance (MR) image reconstruction. Nevertheless, building powerful and robust deep learning models requires collecting large and diverse datasets from multi...

Significance of Artificial Intelligence in the Study of Virus-Host Cell Interactions.

Biomolecules
A highly critical event in a virus's life cycle is successfully entering a given host. This process begins when a viral glycoprotein interacts with a target cell receptor, which provides the molecular basis for target virus-host cell interactions for...

DeepPGD: A Deep Learning Model for DNA Methylation Prediction Using Temporal Convolution, BiLSTM, and Attention Mechanism.

International journal of molecular sciences
As part of the field of DNA methylation identification, this study tackles the challenge of enhancing recognition performance by introducing a specialized deep learning framework called DeepPGD. DNA methylation, a crucial biological modification, pla...

AI-Assisted Rational Design and Activity Prediction of Biological Elements for Optimizing Transcription-Factor-Based Biosensors.

Molecules (Basel, Switzerland)
The rational design, activity prediction, and adaptive application of biological elements (bio-elements) are crucial research fields in synthetic biology. Currently, a major challenge in the field is efficiently designing desired bio-elements and acc...

Social Type-Aware Navigation Framework for Mobile Robots in Human-Shared Environments.

Sensors (Basel, Switzerland)
As robots become increasingly common in human-populated environments, they must be perceived as social beings and behave socially. People try to preserve their own space during social interactions with others, and this space depends on a variety of f...