AIMC Topic: Algorithms

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BiRNN-DDI: A Drug-Drug Interaction Event Type Prediction Model Based on Bidirectional Recurrent Neural Network and Graph2Seq Representation.

Journal of computational biology : a journal of computational molecular cell biology
Research on drug-drug interaction (DDI) prediction, particularly in identifying DDI event types, is crucial for understanding adverse drug reactions and drug combinations. This work introduces a Bidirectional Recurrent Neural Network model for DDI ev...

Subgraph-level federated graph neural network for privacy-preserving recommendation with meta-learning.

Neural networks : the official journal of the International Neural Network Society
Graph neural networks (GNN) are widely used in recommendation systems, but traditional centralized methods raise privacy concerns. To address this, we introduce a federated framework for privacy-preserving GNN-based recommendations. This framework al...

Optimal synchronization with L-gain performance: An adaptive dynamic programming approach.

Neural networks : the official journal of the International Neural Network Society
This paper studies an optimal synchronous control protocol design for nonlinear multi-agent systems under partially known dynamics and uncertain external disturbance. Under some mild assumptions, Hamilton-Jacobi-Isaacs equation is derived by the perf...

SFPL: Sample-specific fine-grained prototype learning for imbalanced medical image classification.

Medical image analysis
Imbalanced classification is a common and difficult task in many medical image analysis applications. However, most existing approaches focus on balancing feature distribution and classifier weights between classes, while ignoring the inner-class het...

Single-cell RNA sequencing data analysis utilizing multi-type graph neural networks.

Computers in biology and medicine
Single-cell RNA sequencing (scRNA-seq) is the sequencing technology of a single cell whose expression reflects the overall characteristics of the individual cell, facilitating the research of problems at the cellular level. However, the problems of s...

An artificial intelligence-enabled electrocardiogram algorithm for the prediction of left atrial low-voltage areas in persistent atrial fibrillation.

Journal of cardiovascular electrophysiology
OBJECTIVES: We aimed to construct an artificial intelligence-enabled electrocardiogram (ECG) algorithm that can accurately predict the presence of left atrial low-voltage areas (LVAs) in patients with persistent atrial fibrillation.

A New Fingerprint and Graph Hybrid Neural Network for Predicting Molecular Properties.

Journal of chemical information and modeling
Machine learning plays a role in accelerating drug discovery, and the design of effective machine learning models is crucial for accurately predicting molecular properties. Characterizing molecules typically involves the use of molecular fingerprints...

Integration of Tracking, Re-Identification, and Gesture Recognition for Facilitating Human-Robot Interaction.

Sensors (Basel, Switzerland)
For successful human-robot collaboration, it is crucial to establish and sustain quality interaction between humans and robots, making it essential to facilitate human-robot interaction (HRI) effectively. The evolution of robot intelligence now enabl...

Utilizing High-Resolution Imaging and Artificial Intelligence for Accurate Leaf Wetness Detection for the Strawberry Advisory System (SAS).

Sensors (Basel, Switzerland)
In strawberry cultivation, precise disease management is crucial for maximizing yields and reducing unnecessary fungicide use. Traditional methods for measuring leaf wetness duration (LWD), a critical factor in assessing the risk of fungal diseases s...