A comprehensive review of machine learning algorithms and their application in geriatric medicine: present and future
The increasing access to health data worldwide is driving a resurgence in machine learning
research, including data-hungry deep learning algorithms. More computationally efficient …
research, including data-hungry deep learning algorithms. More computationally efficient …
Sparse graphs-based dynamic attention networks
R Chen, K Lin, B Hong, S Zhang, F Yang - Heliyon, 2024 - cell.com
In previous research, the prevailing assumption was that Graph Neural Networks (GNNs)
precisely depicted the interconnections among nodes within the graph's architecture …
precisely depicted the interconnections among nodes within the graph's architecture …
Companion animal disease diagnostics based on literal-aware medical knowledge graph representation learning
Knowledge graph (KG) embedding has been used to benefit the diagnosis of animal
diseases by analyzing electronic medical records (EMRs), such as notes and veterinary …
diseases by analyzing electronic medical records (EMRs), such as notes and veterinary …
Applying precision medicine principles to the management of multimorbidity: the utility of comorbidity networks, graph machine learning, and knowledge graphs
The current management of patients with multimorbidity is suboptimal, with either a single-
disease approach to care or treatment guideline adaptations that result in poor adherence …
disease approach to care or treatment guideline adaptations that result in poor adherence …
A counterfactual inference-based social network user-alignment algorithm
L **ng, Y Huang, Q Zhang, H Wu… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
User alignment refers to linking a user's accounts across multiple social networks, which is
important for studying community discovery, recommendation systems, and other related …
important for studying community discovery, recommendation systems, and other related …
Motion states identification of underwater glider based on complex networks and graph convolutional networks
W Guo, X Sun, D Lv, W Ma, W Niu, Z Gao… - … Journal of Nonlinear …, 2024 - pubs.aip.org
Underwater glider (UG) plays an important role in ocean observation and exploration for a
more efficient and deeper understanding of complex ocean environment. Timely identifying …
more efficient and deeper understanding of complex ocean environment. Timely identifying …
Transitivity-preserving graph representation learning for bridging local connectivity and role-based similarity
Graph representation learning (GRL) methods, such as graph neural networks and graph
transformer models, have been successfully used to analyze graph-structured data, mainly …
transformer models, have been successfully used to analyze graph-structured data, mainly …
Introducing diminutive causal structure into graph representation learning
When engaging in end-to-end graph representation learning with Graph Neural Networks
(GNNs), the intricate causal relationships and rules inherent in graph data pose a formidable …
(GNNs), the intricate causal relationships and rules inherent in graph data pose a formidable …
CloudNine: Analyzing Meteorological Observation Impact on Weather Prediction Using Explainable Graph Neural Networks
The impact of meteorological observations on weather forecasting varies with sensor type,
location, time, and other environmental factors. Thus, quantitative analysis of observation …
location, time, and other environmental factors. Thus, quantitative analysis of observation …
Transitivity-Preserving Graph Representation Learning for Bridging Local Connectivity and Role-Based Similarity
OJ Lee - Proceedings of the AAAI Conference on Artificial …, 2024 - ojs.aaai.org
Graph representation learning (GRL) methods, such as graph neural networks and graph
transformer models, have been successfully used to analyze graph-structured data, mainly …
transformer models, have been successfully used to analyze graph-structured data, mainly …