Cheap, Fast, and Good Enough for the Non-biomedical Domain but is It Usable for Clinical Natural Language Processing? Evaluating Crowdsourcing for Clinical Trial Announcement Named Entity Annotations
Haijun Zhai, Todd Lingren, Louise Deléger, Qi Li, Megan Kaiser, Laura Stoutenborough, Imre Solti · 2012
Building upon previous work from the general crowdsourcing research, this study investigates the usability of crowdsourcing in the clinical NLP domain for annotating medical named entities and entity linkages in a clinical trial announcement (CTA) corpus. The results indicate that crowdsourcing is a feasible, inexpensive, fast, and practical approach to annotate clinical text (without PHI) on large scale for medical named entities. The crowdsourcing program code was released publicly.