Latest Research in Biomedical Text Mining and Ontologies

Top Research Topics in Biomedical Text Mining and Ontologies

• Artificial Intelligence — 4 papers
• Computation and Language — 3 papers
• Biomedical Text Mining and Ontologies — 2 papers
• Computer Vision and Pattern Recognition — 2 papers
• Computational Drug Discovery Methods — 1 papers
• Machine Learning in Healthcare — 1 papers
• Computational Engineering, Finance, and Science — 1 papers
• Topic Modeling — 1 papers

Highest-Cited Papers

1. Mechanistic Discovery in Complex Diseases through Multi-Modal AI and Knowledge Graphs
2. LIDR-TB: large language model-integrated platform for traceable drug repurposing in tuberculosis
3. SurgRAW: Multi-Agent Workflow with Chain of Thought Reasoning for Robotic Surgical Video Analysis
4. SNOMED CT Concept Recommendation from Masked Clinical Context
5. Meddies-PII: A Multilingual Framework for Personally Identifiable Information Extraction in Clinical De-identification
6. Target-Checked Reliability Score Refinement for Video Question Answering
7. Hierarchical conditional memory for cross-vocabulary medical entity linking
8. Building evidence-based knowledge bases from full-text literature for disease-specific biomedical reasoning
9. MiNER: Fine-Tuned Biomedical Natural Language Processing for Malaria Disease Entity Recognition in Clinical Texts
10. Unifying biomedical knowledge in a modern multimodal graph
11. Configurable Semantic Chunking for Biomedical Information Extraction in Retrieval-Augmented Generation
12. Noodle: Semantic Biomedical Literature Discovery and Navigable Publication Graph
13. Automated extraction of key entities from non-english thorax CT reports using machine learning by large context, many-shot Generative AI
14. Vision Language Model Fusion for Explainable Face Recognition
15. What Language Models Know But Don't Say: Non-Generative Prior Extraction for Generalization