@inproceedings{2f278f70eed44508ab04eeb11a1a3cd7,
title = "Detecting privacy-sensitive events in medical text",
abstract = "In this paper, we present a novel semi-supervised technique for finding privacy-sensitive events in clinical text. Unlike traditional semi-supervised methods, we do not require large amounts of unannotated data. Instead, our approach relies on information contained in the hierarchical structure of a large medical encyclopedia.",
keywords = "Active learning, Computer security, Concept identification, Domain knowledge, Health informatics, Natural language processing, SNOMED CT, Semi-supervision, Set expansion",
author = "Prateek Jindal and Gunter, \{Carl A.\} and Dan Roth",
note = "Publisher Copyright: Copyright {\textcopyright} 2014 ACM.; 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics, ACM BCB 2014 ; Conference date: 20-09-2014 Through 23-09-2014",
year = "2014",
month = sep,
day = "20",
doi = "10.1145/2649387.2662451",
language = "English (US)",
series = "ACM BCB 2014 - 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics",
publisher = "Association for Computing Machinery",
pages = "617--620",
booktitle = "ACM BCB 2014 - 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics",
address = "United States",
}