Dual-Level Interaction Aware Heterogeneous Graph Neural Network for Medicine Package Recommendation

Information Science, Computer Science, Artificial Intelligence, Medicine, Environmental and Public Health, Pharmacy,
medicine package recommendation   dual-level interaction   heterogeneous graph neural network   electronic health records   clinical decision-making  

Research on Medical Package Recommendation Systems: Heterogeneous Graph Neural Network Based on Dual-Level Interaction Awareness With the widespread application of electronic health records (EHRs) in the medical field, how to mine potential and valuable medical knowledge to support clinical decision-making has become an important research direction...

Predicting Drug-Target Affinity by Learning Protein Knowledge from Biological Networks

Information Science, Computer Science, Artificial Intelligence, Life Sciences, Biochemistry, Bioengineering, Biophysics,
drug-target affinity   variational graph autoencoders   graph convolutional network   protein-protein interaction  

Predicting Drug-Target Affinity Based on Learning Protein Knowledge from Biological Networks Background The prediction of drug-target affinity (DTA) plays a crucial role in drug discovery. Efficient and accurate DTA prediction can significantly reduce the time and economic costs of new drug development. In recent years, the explosive development of...

An Explainable and Personalized Cognitive Reasoning Model Based on Knowledge Graph: Toward Decision Making for General Practice

An Explainable and Personalized Cognitive Reasoning Model Based on Knowledge Graph: Toward Decision Making for General Practice

Information Science, Computer Science, Artificial Intelligence, Medicine, Infectious Diseases,
knowledge graph   cognitive reasoning   explainability   general practice   electronic health records  

An Explainable and Personalized Cognitive Reasoning Model Based on Knowledge Graph: Toward Decision Making for General Practice Background General medicine, as an important part of community and family healthcare, covers different ages, genders, organ systems, and various diseases. Its core concept is human-centered, family-based, emphasizing long-...

Knowledge-Enhanced Graph Topic Transformer for Explainable Biomedical Text Summarization

Information Science, Computer Science, Artificial Intelligence, Medicine, Environmental and Public Health, Medical Laboratory Science, Life Sciences, Biochemistry,
biomedical text summarization   domain knowledge   graph neural network   explainability   pre-trained language models  

Application of Knowledge-Enhanced Graph Topic Transformer in Interpretable Biomedical Text Summarization Research Background Due to the continuous increase in the volume of biomedical literature, the task of automatic biomedical text summarization has become increasingly important. In 2021 alone, 1,767,637 articles were published in the PubMed data...

Graph Neural Networks with Multiple Prior Knowledge for Multi-omics Data Analysis

Graph Neural Networks with Multiple Prior Knowledge for Multi-omics Data Analysis

Information Science, Computer Science, Artificial Intelligence, Medicine, Environmental and Public Health, Oncology, Life Sciences, Cell Biology, Genetics,
graph neural networks   multi-omics data   contrastive learning   biological knowledge   cancer molecular classification  

Multiple Prior Knowledge Graph Neural Network in Multi-Omics Data Analysis Background Introduction Precision medicine is an important field for the future of healthcare as it provides personalized treatment plans for patients, improving treatment outcomes and reducing costs. For instance, due to the complex clinical, pathological, and molecular cha...

Stage-Aware Hierarchical Attentive Relational Network for Diagnosis Prediction

Information Science, Computer Science, Artificial Intelligence, Medicine, Medical Laboratory Science,
Stage-Aware   Hierarchical Attention   Diagnosis Prediction   Electronic Health Records   Knowledge Graphs   Relational Graph Neural Networks  

Application of Hierarchical Attentive Relational Network in Diagnostic Prediction In recent years, Electronic Health Records (EHR) have become extremely valuable in improving medical decision-making, online disease detection, and monitoring. At the same time, deep learning methods have also achieved great success in utilizing EHR for health risk pr...