Presenter: Debra Ozga, National Library of Medicine
In the context of MEDLINE®, the Medical Text Indexer (MTI) system consists of automatic machine-learning software for applying alternative methods of discovering MeSH headings for citation titles and abstracts and then combining them into an ordered list of recommended indexing terms. This Webinar will describe the structure and workflow of the NLM Index Section as it relates to the ingestion of an ever increasing number of articles, citations and abstracts which require indexing in MEDLINE®. MTI and similar applications fall under NLM’s Indexing Initiative (II) which is designed to investigate methods for automatic and assisted indexing to enhance access to NLM document collections. MTI, and its newer version, MTIFL (Medical Text Indexer First Line) are solutions used, in conjunction with reviewers, in completing the individual steps/tasks that result in a finished citation/abstract in MEDLINE®, searchable through PubMed.
As Head of the Index Section at the National Library of Medicine, Deborah Ozga manages the unit responsible for MEDLINE indexing and quality assurance. Prior to joining NLM, Ms. Ozga held a variety of administrative and information specialist positions, at The Catholic University of America Libraries, the NIH Library, and the Library of Congress, and taught the core course on information access as an adjunct faculty member at the University of Maryland iSchool at College Park.
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