Lana Yeganova

United States National Library of Medicine

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Total Citations

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About

Lana Yeganova is a leading researcher in biomedical natural language processing (NLP) and information retrieval, with a focus on advancing the accessibility and analysis of scientific literature. Her major contributions lie in developing algorithms and systems that extract, normalize, and link biomedical entities—such as genes, diseases, and chemicals—from vast text corpora, significantly enhancing the utility of resources like PubMed. She has been instrumental in creating tools for named entity recognition, relation extraction, and document classification, which underpin critical applications in drug discovery and clinical decision support. With over 1,500 citations across her body of work, Yeganova’s impact is evident in her widely adopted methods for text mining and ontology-based indexing. Notably, she has co-authored influential reports on AI symposiums, including the 2012 AAAI Fall Symposium Series, demonstrating her leadership in bridging AI and biomedicine. Her achievements include key roles in the BioCreative community challenges, where her systems consistently set benchmarks for performance. Through her research, Yeganova has empowered scientists to navigate the ever-growing biomedical literature with unprecedented speed and accuracy.