AIMC Topic: Neural Networks, Computer

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Two-step interpretable modeling of ICU-AIs.

Artificial intelligence in medicine
We present a novel methodology for integrating high resolution longitudinal data with the dynamic prediction capabilities of survival models. The aim is two-fold: to improve the predictive power while maintaining the interpretability of the models. T...

Photocatalytic decomposition of metronidazole by zinc hexaferrite coated with bismuth oxyiodide magnetic nanocomposite: Advanced modelling and optimization with artificial neural network.

Chemosphere
The objective of the present study was to employ a green synthesis method to produce a sustainable ZnFeO/BiOI nanocomposite and evaluate its efficacy in the photocatalytic degradation of metronidazole (MNZ) from aqueous media. An artificial neural ne...

Prediction of hospital mortality among critically ill patients in a single centre in Asia: comparison of artificial neural networks and logistic regression-based model.

Hong Kong medical journal = Xianggang yi xue za zhi
INTRODUCTION: This study compared the performance of the artificial neural network (ANN) model with the Acute Physiologic and Chronic Health Evaluation (APACHE) II and IV models for predicting hospital mortality among critically ill patients in Hong ...

GraphKM: machine and deep learning for K prediction of wildtype and mutant enzymes.

BMC bioinformatics
Michaelis constant (K) is one of essential parameters for enzymes kinetics in the fields of protein engineering, enzyme engineering, and synthetic biology. As overwhelming experimental measurements of K are difficult and time-consuming, prediction of...

Fatty liver classification via risk controlled neural networks trained on grouped ultrasound image data.

Scientific reports
Ultrasound imaging is a widely used technique for fatty liver diagnosis as it is practically affordable and can be quickly deployed by using suitable devices. When it is applied to a patient, multiple images of the targeted tissues are produced. We p...

HGCMorph: joint discontinuity-preserving and pose-learning via GNN and capsule networks for deformable medical images registration.

Physics in medicine and biology
This study aims to enhance medical image registration by addressing the limitations of existing approaches that rely on spatial transformations through U-Net, ConvNets, or Transformers. The objective is to develop a novel architecture that combines C...

Self-replicating artificial neural networks give rise to universal evolutionary dynamics.

PLoS computational biology
In evolutionary models, mutations are exogenously introduced by the modeler, rather than endogenously introduced by the replicator itself. We present a new deep-learning based computational model, the self-replicating artificial neural network (SeRAN...

Emergence of Emotion Selectivity in Deep Neural Networks Trained to Recognize Visual Objects.

PLoS computational biology
Recent neuroimaging studies have shown that the visual cortex plays an important role in representing the affective significance of visual input. The origin of these affect-specific visual representations is debated: they are intrinsic to the visual ...

DEW: A wavelet approach of rare sound event detection.

PloS one
This paper presents a novel sound event detection (SED) system for rare events occurring in an open environment. Wavelet multiresolution analysis (MRA) is used to decompose the input audio clip of 30 seconds into five levels. Wavelet denoising is the...

Elevator block brake structural optimization design based on an approximate model.

PloS one
An Aquila optimizer-back propagation (AO-BP) neural network was used to establish an approximate model of the relationship between the design variables and the optimization objective to improve elevator block brake capabilities and achieve a lightwei...