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Graph neural network modelling as a potentially effective method for predicting and analyzing procedures based on patients' diagnoses

  • Published:2022-09 Issue: Volume:131 Page:102359
  • ISSN:0933-3657
  • Container-title:Artificial Intelligence in Medicine
  • language:en
  • Short-container-title:Artificial Intelligence in Medicine

Author:

Diaz Ochoa Juan G.,Mustafa Faizan E

Publisher

Elsevier BV

Subject

Artificial Intelligence,Medicine (miscellaneous)

Reference27 articles.

1. AI and machine learning paradigms for health monitoring system: intelligent data analytics;Malik,2021

2. Healthcare data analytics;Reddy,2015

3. From personalization to patient centered systems toxicology and pharmacology;Diaz Ochoa;Comput Toxicol,2019

4. AHRQ quality indicators;Farquhar,2008

5. Conceptual graph representation framework for ICD-10;Hema;Procedia Comput Sci,2015

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2. TACCO: Task-guided Co-clustering of Clinical Concepts and Patient Visits for Disease Subtyping based on EHR Data;Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2024-08-24

3. HealthGAT: Node Classifications in Electronic Health Records using Graph Attention Networks;2024 IEEE/ACM Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE);2024-06-19

4. Parkinson’s Disease Classification Using Contrastive Graph Cross-View Learning with Multimodal Fusion of Spect Images and Clinical Features;2024 IEEE International Symposium on Biomedical Imaging (ISBI);2024-05-27

5. Identifying pharmaceutical technology opportunities from the perspective of adverse drug reactions: Machine learning in multilayer networks;Technological Forecasting and Social Change;2024-04
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