Text Mining and Natural Language Processing (NLP) Scientific Interest Group

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With the increasing availability of text information related to diverse research fields across the NIH Intramural Research Program, the domain of biomedical text mining and Natural Language Processing (NLP) has seen a tremendous growth. Some examples of how researchers across campus utilize NLP are improving literature search in PubMed, automatic entity extraction from scientific articles for scaling up manual curation, etc. Researchers are building knowledge discovery resources for improved literature search and network analysis of scientific literature. Furthermore, text mining techniques are core to computational biology including genomics and other “-omics” analysis.

In addition to literature mining, there are many emerging clinical applications of text mining. Electronic health records (EHRs) and parsing of EHR data have captured much attention among clinical professionals. Other areas of clinical relevance that can greatly benefit from NLP techniques include patient cohort identification, clinical question answering, health care quality research, precision medicine, bio surveillance, drug development, text analysis. The text mining and NLP SIG provides clinicians on campus more opportunities to learn and network with text mining researchers.

Several institutes on campus are doing text mining, but these groups can benefit from the opportunities to collaborate and learn from each other’s work via the NIH Text Mining and Natural Language Processing (NLP) Scientific Interest Group.

Organizing Committee
Lana Yeganova , Ph.D., NLM
Qingyu Chen , Ph.D., NLM
Ayah Zirikly , Ph.D., Clinical Center

Zhiyong.Lu@nih.gov Zhiyong Lu, Ph.D. https://www.ncbi.nlm.nih.gov/research/bionlp/ ddemner@mail.nih.gov Dina Demner-Fushman, M.D., Ph.D. https://lhncbc.nlm.nih.gov/personnel/dina-demner-fushman Scientific Interest Groups Lana Yeganova, Ph.D. https://list.nih.gov/cgi-bin/wa.exe?A0=NATURAL-LANGAUGE-PROCESSING