AIMC Topic: Neural Networks, Computer

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A lightweight network for brain MRI segmentation.

Scientific reports
Brain MRI segmentation plays a crucial role in medical imaging, aiding in the identification and monitoring of brain diseases. This research presents a novel deep learning-based framework designed to achieve high segmentation accuracy while maintaini...

A novel framework for COPD management in cyber-physical systems using machine learning.

Scientific reports
Chronic Obstructive Pulmonary Disease (COPD) exacerbations pose significant challenges to healthcare systems due to their unpredictable nature and severe impact on patients. Current COPD prediction models often lack real-time capabilities and fail to...

Aligning machines and minds: neural encoding for high-level visual cortices based on image captioning task.

Journal of neural engineering
Neural encoding of visual stimuli aims to predict brain responses in the visual cortex to different external inputs. Deep neural networks trained on relatively simple tasks such as image classification have been widely applied in neural encoding stud...

MSDC: Aspect-level sentiment analysis model based on multi-scale dual-channel feature fusion.

PloS one
Aspect-level sentiment analysis is a significant task in the field of natural language processing. It can process text in a fine-grained manner to predict the sentiment polarity of a specific aspect word in a sentence. However, existing single-channe...

Optimizing network bandwidth slicing identification: NADAM-enhanced CNN and VAE data preprocessing for enhanced interpretability.

PloS one
Communication networks of the future will rely heavily on network slicing (NS), a technology that enables the creation of distinct virtual networks within a shared physical infrastructure. This capability is critical for meeting the diverse quality o...

Multidimensional trophoblast invasion assessment by combining 3D in vitro modeling and deep learning analysis.

NPJ systems biology and applications
Infertility affects millions of couples worldwide, and in vitro fertilization is a key therapeutic strategy for achieving parenthood. Despite advances, the first IVF attempt fails in ~60% of patients, highlighting the need for innovative solutions to...

A microneedle-based integrated three-electrode system for pesticide detection using machine learning.

The Analyst
Pesticides contribute to enhanced agricultural productivity, yet excessive residues pose significant health risks to humans as they persist even after washing, making their detection in crops critically important. In this study, we employed 3D-printe...

An Explainable 3D-Deep Learning Model for EEG Decoding in Brain-Computer Interface Applications.

International journal of neural systems
Decoding electroencephalographic (EEG) signals is of key importance in the development of brain-computer interface (BCI) systems. However, high inter-subject variability in EEG signals requires user-specific calibration, which can be time-consuming a...

Automating Deep Learning-Based Generation and Evaluation of De Novo Chemical Reaction with ChemRxnSAGE.

Journal of chemical information and modeling
The generation and evaluation of chemical reactions remain challenging with limited comprehensive studies addressing these issues. We introduce the ical Reaction () ystematic ssessment of eneration and valuation () framework, an adaptable end-to-end ...

A performance analysis of convolutional autoencoder modified WaveGAN architectures for realistic 12 lead electrocardiogram synthesis.

Scientific reports
The burgeoning necessity for copious and diverse electrocardiogram (ECG) datasets for deep learning applications in clinical diagnostics has been impeded by the confidential nature of patient data. Related works have shown the effectiveness of additi...