Results 191 to 200 of about 5,698,498 (295)

The classification of brain network for major depressive disorder patients based on deep graph convolutional neural network. [PDF]

Front Hum Neurosci, 2023
Zhu M, Quan Y, He X.
europepmc   +1 more source

Why Physics Still Matters: Improving Machine Learning Prediction of Material Properties With Phonon‐Informed Datasets

Advanced Intelligent Discovery, EarlyView.
Phonons‐informed machine‐learning predictive models are propitious for reproducing thermal effects in computational materials science studies. Machine learning (ML) methods have become powerful tools for predicting material properties with near first‐principles accuracy and vastly reduced computational cost.
Pol Benítez, Cibrán López, Edgardo Saucedo, Teruyasu Mizoguchi, Claudio Cazorla   +4 more
wiley   +1 more source

3D reconstruction of spatial transcriptomics with spatial pattern enhanced graph convolutional neural network. [PDF]

Brief Bioinform
Tang C, Zhou Y, Xiao X, Dong L, Yu L, Li Q, Xiao G, Xu L.   +7 more
europepmc   +1 more source

GCNCMI: A Graph Convolutional Neural Network Approach for Predicting circRNA-miRNA Interactions. [PDF]

Front Genet, 2022
He J, Xiao P, Chen C, Zhu Z, Zhang J, Deng L.   +5 more
europepmc   +1 more source

When Biology Meets Medicine: A Perspective on Foundation Models

Advanced Intelligent Discovery, EarlyView.
Artificial intelligence, and foundation models in particular, are transforming life sciences and medicine. This perspective reviews biological and medical foundation models across scales, highlighting key challenges in data availability, model evaluation, and architectural design.
Kunying Niu, Yuxing Wang, Limin Zou, Jing Huang   +3 more
wiley   +1 more source

Superpixel-based graph convolutional neural network for polarimetric synthetic aperture radar image classification. [PDF]

Sci Rep
Imani M.
europepmc   +1 more source

Decoding Visual fMRI Stimuli from Human Brain Based on Graph Convolutional Neural Network. [PDF]

Brain Sci, 2022
Meng L, Ge K.
europepmc   +1 more source

Distribution Network Operational Situation Perception Technology Based on Graph Convolutional Neural Network-Enhanced Digital Twin Model

Currently, traditional monitoring methods based on physical models and SCADA static data struggle to achieve real-time insight, trend prediction, and proactive early warning of system operational states.
Hao Bai, Yipeng Liu, Wei Li
core   +1 more source

A Robust Deep Temporal Causal Discovery Platform for Single‐Cell Gene Regulatory Network Reconstruction

Advanced Intelligent Discovery, EarlyView.
scTIGER2.0 is a deep‐learning framework that infers gene regulatory networks from single‐cell RNA sequencing data. By integrating correlation, pseudotime ordering, deep learning and bootstrap‐based significance testing, it reduces false positives and reveals directional gene interactions.
Nishi Gupta, Madison Dautle, Shaoqiang Zhang, Yong Chen   +3 more
wiley   +1 more source

THGC_MDA: a method for predicting the associations between m¹A modification and diseases based on ternary heterogeneous network and graph convolutional neural network. [PDF]

Front Genet
Gao H, Zhou X, Bai L, Yang H, Liu F.
europepmc   +1 more source