AIMC Topic: Neural Networks, Computer

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A holistic physics-informed neural network solution for precise destruction of breast tumors using focused ultrasound on a realistic breast model.

Mathematical biosciences and engineering : MBE
This study presented a novel approach for the precise ablation of breast tumors using focused ultrasound (FUS), leveraging a physics-informed neural network (PINN) integrated with a realistic breast model. FUS has shown significant promise in treatin...

Dual-channel lightweight GAN for enhancing color retinal images with noise suppression and structural protection.

Journal of the Optical Society of America. A, Optics, image science, and vision
As we all know, suppressing noise while maintaining detailed structure has been a challenging problem in the field of image enhancement, especially for color retinal images. In this paper, a dual-channel lightweight GAN named dilated shuffle generati...

[Bowel Sounds Detection Method Based on ResNet-BiLSTM and Attention Mechanism].

Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation
Bowel sounds can reflect the movement and health status of the gastrointestinal tract. However, the traditional manual auscultation method has subjective deviation and is time-consuming and labor-intensive. In order to better assist doctors in diagno...

DockingGA: enhancing targeted molecule generation using transformer neural network and genetic algorithm with docking simulation.

Briefings in functional genomics
Generative molecular models generate novel molecules with desired properties by searching chemical space. Traditional combinatorial optimization methods, such as genetic algorithms, have demonstrated superior performance in various molecular optimiza...

Nmix: a hybrid deep learning model for precise prediction of 2'-O-methylation sites based on multi-feature fusion and ensemble learning.

Briefings in bioinformatics
RNA 2'-O-methylation (Nm) is a crucial post-transcriptional modification with significant biological implications. However, experimental identification of Nm sites is challenging and resource-intensive. While multiple computational tools have been de...

AIGen: an artificial intelligence software for complex genetic data analysis.

Briefings in bioinformatics
The recent development of artificial intelligence (AI) technology, especially the advance of deep neural network (DNN) technology, has revolutionized many fields. While DNN plays a central role in modern AI technology, it has rarely been used in gene...

Precision DNA methylation typing via hierarchical clustering of Nanopore current signals and attention-based neural network.

Briefings in bioinformatics
Decoding DNA methylation sites through nanopore sequencing has emerged as a cutting-edge technology in the field of DNA methylation research, as it enables direct sequencing of native DNA molecules without the need for prior enzymatic or chemical tre...

Adversarial regularized autoencoder graph neural network for microbe-disease associations prediction.

Briefings in bioinformatics
BACKGROUND: Microorganisms inhabit various regions of the human body and significantly contribute to numerous diseases. Predicting the associations between microbes and diseases is crucial for understanding pathogenic mechanisms and informing prevent...

A multichannel graph neural network based on multisimilarity modality hypergraph contrastive learning for predicting unknown types of cancer biomarkers.

Briefings in bioinformatics
Identifying potential cancer biomarkers is a key task in biomedical research, providing a promising avenue for the diagnosis and treatment of human tumors and cancers. In recent years, several machine learning-based RNA-disease association prediction...

siRNADiscovery: a graph neural network for siRNA efficacy prediction via deep RNA sequence analysis.

Briefings in bioinformatics
The clinical adoption of small interfering RNAs (siRNAs) has prompted the development of various computational strategies for siRNA design, from traditional data analysis to advanced machine learning techniques. However, previous studies have inadequ...