@inproceedings{aebff04aca7445ae9f2f463d88d7ede7,
title = "“Devils Are in the Details”: Annotating Specificity of Clinical Advice from Medical Literature",
abstract = "Prior studies have raised concerns over specificity issues in clinical advice. Lacking specificity — explicitly discussed detailed information — may affect the quality and implementation of clinical advice in medical practice. In this study, we developed and validated a fine-grained annotation schema to describe different aspects of specificity in clinical advice extracted from medical research literature. We also presented our initial annotation effort and discussed future directions towards an NLP-based specificity analysis tool for summarizing and verifying the details in clinical advice.",
author = "Yingya Li and Bei Yu",
note = "Funding Information: This research is supported by the US National Science Foundation under grant 1952353 and the Syracuse University CUSE Grant. Publisher Copyright: {\textcopyright} 2022 Association for Computational Linguistics.; 2nd Workshop on Understanding Implicit and Underspecified Language, UnImplicit 2022 ; Conference date: 15-07-2022",
year = "2022",
language = "English (US)",
series = "UnImplicit 2022 - 2nd Workshop on Understanding Implicit and Underspecified Language, Proceedings of the Workshop",
publisher = "Association for Computational Linguistics (ACL)",
pages = "17--21",
editor = "Valentina Pyatkin and Daniel Fried and Talita Anthonio",
booktitle = "UnImplicit 2022 - 2nd Workshop on Understanding Implicit and Underspecified Language, Proceedings of the Workshop",
address = "United States",
}