Using Amazon's Mechanical Turk for Annotating Medical Named Entities
Related Experiment Video
Updated: May 30, 2026

07:50
A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
Published on: September 20, 2018
Meliha Yetisgen-Yildiz1, Imre Solti, Fei Xia
1Biomedical & Health Informatics, School of Medicine, University of Washington, Seattle, WA.
AMIA ... Annual Symposium Proceedings. AMIA Symposium
|July 26, 2011
Abstract:
Amazon's Mechanical Turk (AMT) service is becoming increasingly popular in Natural Language Processing (NLP) research. In this poster, we report our findings in using AMT to annotate biomedical text extracted from clinical trial descriptions with three entity types: medical condition, medication, and laboratory test. We also describe our observations on AMT workers' annotations.