This paper is in the following e-collection/theme issue:

Theme Issue 2021: Health Natural Language Processing and Applications (16) Natural Language Processing (828) Ontologies, Classifications, and Coding (282)

Published on in Vol 9, No 6 (2021): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/28277, first published .
Drug-Drug Interaction Predictions via Knowledge Graph and Text Embedding: Instrument Validation Study

Drug-Drug Interaction Predictions via Knowledge Graph and Text Embedding: Instrument Validation Study

Drug-Drug Interaction Predictions via Knowledge Graph and Text Embedding: Instrument Validation Study

Authors of this article:

Meng Wang1, 2 Author Orcid Image ;   Haofen Wang3 Author Orcid Image ;   Xing Liu4 Author Orcid Image ;   Xinyu Ma1 Author Orcid Image ;   Beilun Wang1 Author Orcid Image
Article Authors Cited by (12) Tweetations (4) Metrics

Journals

  1. Kim J, Shin M. A Knowledge Graph Embedding Approach for Polypharmacy Side Effects Prediction. Applied Sciences 2023;13(5):2842 View
  2. Pavel A, Saarimäki L, Möbus L, Federico A, Serra A, Greco D. The potential of a data centred approach & knowledge graph data representation in chemical safety and drug design. Computational and Structural Biotechnology Journal 2022;20:4837 View
  3. Rodríguez-Revello J, Barba-González C, Rybinski M, Navas-Delgado I. KNIT: Ontology reusability through knowledge graph exploration. Expert Systems with Applications 2023;228:120239 View
  4. Wu J, Ning Z, Ding Y, Wang Y, Peng Q, Fu L. KGETCDA: an efficient representation learning framework based on knowledge graph encoder from transformer for predicting circRNA-disease associations. Briefings in Bioinformatics 2023;24(5) View
  5. Cai L, Li J, Lv H, Liu W, Niu H, Wang Z. Integrating domain knowledge for biomedical text analysis into deep learning: A survey. Journal of Biomedical Informatics 2023;143:104418 View
  6. Alvarez-Mamani E, Dechant R, Beltran-Castañón C, Ibáñez A. Graph embedding on mass spectrometry- and sequencing-based biomedical data. BMC Bioinformatics 2024;25(1) View
  7. Dagenais S, Lee C, Cronenberger C, Wang E, Sahasrabudhe V. Proposing a framework to quantify the potential impact of pharmacokinetic drug–drug interactions caused by a new drug candidate by using real world data about the target patient population. Clinical and Translational Science 2024;17(3) View
  8. Hauben M, Rafi M, Abdelaziz I, Hassanzadeh O. Knowledge Graphs in Pharmacovigilance: A Scoping Review. Clinical Therapeutics 2024;46(7):544 View
  9. Gallego F, Ruas P, Couto F, Veredas F. Enhancing cross-encoders using knowledge graph hierarchy for medical entity linking in zero- and few-shot scenarios. Knowledge-Based Systems 2025;314:113211 View

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  1. Talukder A, Selg E, Fernandez R, Raj T, Waghmare A, Haas R. Big Data Analytics. View

Conference Proceedings

  1. Li W, Ma Y, Su J, Zhang H. 2023 6th International Conference on Signal Processing and Machine Learning (SPML). Visualization of Adverse Drug Reactions Based on the Knowledge Graphs View
  2. Galhotra Y, Ding Y, Shen L, Wu H, Chen T, Zhou K. Proceedings of the 15th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics. Towards Instructing Disease-Drug Link Prediction with Social Determinants of Health View