AIMC Topic: Neural Networks, Computer

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Automated hypoxia and apnea identification for neonates via enhanced respiratory signal modeling with deep learning.

Scientific reports
Neonatal respiratory monitoring is crucial for assessing breathing patterns, but the lack of real-time clinical data limits the development of machine learning (ML) models. This study provides a synthetic signal generation framework to replicate infa...

MCLCBA: multi-view contrastive learning network for RNA methylation site prediction.

BMC bioinformatics
BACKGROUND: RNA methylation (RM) regulates gene expression regulation, RNA stability, and protein translation. Accurate prediction of RM modification sites is essential for understanding their biological functions. However, existing wet-lab detection...

MPIDNN-GPPI: multi-protein language model with an improved deep neural network for generalized protein‒protein interaction prediction.

BMC genomics
Predicting protein‒protein interactions (PPIs) plays a crucial role in understanding biological processes. Although biological experimental methods can identify PPIs, they are costly, time-consuming, labor-intensive, and often lack stability. In cont...

A multi-geometric graph fusion network for protein-ligand affinity prediction.

Physical chemistry chemical physics : PCCP
Protein-ligand binding affinity prediction plays a crucial role in drug discovery. While recent works use two-dimensional graph neural networks to improve affinity prediction, we find that the three-dimensional geometric information of proteins and l...

Super-resolution reconstruction of OCT images based on frequency and spatial information in adversarial neural networks.

Physics in medicine and biology
Optical coherence tomography (OCT) has a wide range of applications in the diagnosis and treatment of diseases such as heart and ophthalmic diseases. However, the inherent limitations of imaging hardware, low spatial sampling rates, and noise severel...

Universal black-box attacks against a third-party Alzheimer's diagnostic system.

Biomedical physics & engineering express
Artificial intelligence (AI) systems are increasingly used in medical imaging for disease diagnosis, yet their vulnerability to adversarial attacks poses significant risks for clinical deployment. In this work, we systematically evaluate the suscepti...

Iterative reconstruction of industrial positron images with generative networks.

PloS one
Positron imaging has shown great potential in industrial non-destructive testing due to its high sensitivity and ability to reveal internal structures of complex components. However, reconstructing high-quality images from positron emission data rema...

SMG-Net: A lightweight modular architecture for fine-grained crack segmentation in ancient wooden structures.

PloS one
To improve the accuracy and efficiency of crack segmentation in ancient wooden structures, we propose a lightweight deep neural network architecture, termed SMG-Net. The core innovation of this model lies in its multi-cooperative perception mechanism...

ATR-FTIR Spectroscopy of Saliva and Machine Learning as a Screening Test for Sjögren Disease.

Analytical chemistry
Sjögren's disease is often an underdiagnosed autoimmune condition that primarily affects the exocrine glands, resulting in symptoms such as dry eyes and dry mouth. Diagnostic challenges stem from nonspecific symptoms, the absence of definitive biomar...

A Practical Guide to Transition State Analysis in Biomolecular Simulations with TS-DAR.

The journal of physical chemistry. B
Conformational changes essential for protein function involve transitions through multiple short-lived, high-energy states within the complex free energy landscape. While existing methods, such as Markov State Models and non-Markovian approaches buil...