Wikimedia Foundation Annual Plan/2024-2025/Collaboration/AI call/Houcemeddine links

• Construct a biomedical knowledge graph with NLP: https://towardsdatascience.com/construct-a-biomedical-knowledge-graph-with-nlp-1f25eddc54a0
• DBpedia: https://dbpedia.org/page/Tunisia
• Wwwyzzerdd for Wikidata: https://chromewebstore.google.com/detail/wwwyzzerdd-for-wikidata/gfidggfngdnaalpihbdjnfbkfiniookc and https://www.wikidata.org/wiki/Wikidata:Wwwyzzerdd
• PubMed: https://pubmed.ncbi.nlm.nih.gov/7854456/
• MeSH2Matrix: Machine learning-driven biomedical relation classification based on the MeSH keywords of PubMed scholarly publications: https://ceur-ws.org/Vol-3230/paper-07.pdf
• Demo: https://colab.research.google.com/drive/1keSoN8w6fMKAMIcezzXwJIOL_K3OVFEY
• MeSH2Wikidata: A set of tools for the interaction between MeSH keywords, OBO Foundry, and Wikidata for enriching biomedical knowledge: https://doi.org/10.6084/m9.figshare.24438184
• NetMe 2.0: a web-based platform for extracting and modeling knowledge from biomedical literature as a labeled graph: https://doi.org/10.1093/bioinformatics/btae194 and https://netme.click/#/
• Doc-KG: Unstructured documents to knowledge graph construction, identification and validation with Wikidata: https://doi.org/10.1111/exsy.13617