AIMC Topic: Neural Networks, Computer

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Amortized template matching of molecular conformations from cryoelectron microscopy images using simulation-based inference.

Proceedings of the National Academy of Sciences of the United States of America
Characterizing the conformational ensemble of biomolecular systems is key to understand their functions. Cryoelectron microscopy (cryo-EM) captures two-dimensional snapshots of biomolecular ensembles, giving in principle access to thermodynamics. How...

Machine reading and recovery of colors for hemoglobin-related bioassays and bioimaging.

Science advances
Despite advances in machine learning and computer vision for biomedical imaging, machine reading and learning of colors remain underexplored. Color consistency in computer vision, color constancy in human perception, and color accuracy in biomedical ...

GNNMutation: a heterogeneous graph-based framework for cancer detection.

BMC bioinformatics
BACKGROUND: When genes are translated into proteins, mutations in the gene sequence can lead to changes in protein structure and function as well as in the interactions between proteins. These changes can disrupt cell function and contribute to the d...

A hybrid GAN-based deep learning framework for thermogram-based breast cancer detection.

Scientific reports
Breast cancer remains one of the most prevalent and life-threatening diseases among women worldwide, necessitating early and accurate detection methods. Traditional diagnostic approaches often face limitations in sensitivity and specificity, highligh...

Deep learning based rapid X-ray fluorescence signal extraction and image reconstruction for preclinical benchtop X-ray fluorescence computed tomography applications.

Scientific reports
Recent research advances have resulted in an experimental benchtop X-ray fluorescence computed tomography (XFCT) system that likely meets the imaging dose/scan time constraints for benchtop XFCT imaging of live mice injected with gold nanoparticles (...

Optimal graph representations and neural networks for multichannel time series data in seizure phase classification.

Scientific reports
In recent years, several machine-learning (ML) solutions have been proposed to solve the problems of seizure detection, seizure phase classification, seizure prediction, and seizure onset zone (SOZ) localization, achieving excellent performance with ...

Powdery mildew resistance prediction in Barley (Hordeum Vulgare L) with emphasis on machine learning approaches.

Scientific reports
By employing machine-learning models, this study utilizes agronomical and molecular features to predict powdery mildew disease resistance in Barley (Hordeum Vulgare L). A 130-line F8-F9 barley population caused Badia and Kavir to grow at the Gonbad K...

Decreased spinal inhibition leads to undiversified locomotor patterns.

Biological cybernetics
During walking and running, animals display rich and coordinated motor patterns that are generated and controlled within the central nervous system. Previous computational and experimental results suggest that the balance between excitation and inhib...

Mulberry leaf disease detection by CNN-ViT with XAI integration.

PloS one
Mulberry leaf disease detection is vital for maintaining the health and productivity of mulberry crops. In this paper, a novel approach was proposed by integrating explainable artificial intelligence (XAI) techniques with a convolutional neural netwo...

Verification and application of deep learning models in daily sports activities of teenagers.

PloS one
With the development of smart wearable devices and deep learning (DL) technology, the monitoring and analysis of daily sports activities of teenagers face new opportunities. At present, traditional CNN (Convolutional Neural Network) models are mostly...