Harnessing Biomedical Natural Language Processing Tools to Identify Medicinal Plant Knowledge from Historical Texts

Vivekanand Sharma, Wayne Law, Michael J. Balick, Indra Neil Sarkar

Research output: Contribution to conferencePaper

Abstract

The growing amount of data describing historical medicinal uses of plants from digitization efforts provides the opportunity to develop systematic approaches for identifying potential plant-based therapies. However, the task of cataloguing plant use information from natural language text is a challenging task for ethnobotanists. To date, there have been only limited adoption of informatics approaches used for supporting the identification of ethnobotanical information associated with medicinal uses. This study explored the feasibility of using biomedical terminologies and natural language processing approaches for extracting relevant plant-associated therapeutic use information from historical biodiversity literature collection available from the Biodiversity Heritage Library. The results from this preliminary study suggest that there is potential utility of informatics methods to identify medicinal plant knowledge from digitized resources as well as highlight opportunities for improvement.

Original languageAmerican English
StatePublished - Nov 7 2017
EventAmerican Medical Informatics Association (AMIA) 2017 Annual Symposium - Washington, United States
Duration: Nov 4 2017Nov 8 2017

Symposium

SymposiumAmerican Medical Informatics Association (AMIA) 2017 Annual Symposium
Abbreviated titleAMIA 2017
Country/TerritoryUnited States
CityWashington
Period11/4/1711/8/17

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