Abbreviation Detection in Vietnamese Clinical Texts
نویسندگان
چکیده
منابع مشابه
Unsupervised Abbreviation Detection in Clinical Narratives
Clinical narratives in electronic health record systems are a rich resource of patient-based information. They constitute an ongoing challenge for natural language processing, due to their high compactness and abundance of short forms. German medical texts exhibit numerous ad-hoc abbreviations that terminate with a period character. The disambiguation of period characters is therefore an import...
متن کاملAbbreviation and Acronym Disambiguation in Clinical Discourse
Use of abbreviations and acronyms is pervasive in clinical reports despite many efforts to limit the use of ambiguous and unsanctioned abbreviations and acronyms. Due to the fact that many abbreviations and acronyms are ambiguous with respect to their sense, complete and accurate text analysis is impossible without identification of the sense that was intended for a given abbreviation or acrony...
متن کاملA Maximum Entropy Approach to Sentence Boundary Detection of Vietnamese Texts
We present for the first time a sentence boundary detection system for identifying sentence boundaries in Vietnamese texts. The system is based on a maximum entropy model. The training procedure requires no hand-crafted rules, lexicon, or domain-specific information. Given a corpus annotated with sentence boundaries, the model learns to classify each occurrence of potential end-of-sentence punc...
متن کاملNegation and Speculation Detection in Clinical and Review Texts
PhD Thesis written by Noa P. Cruz Díaz at the University of Huelva under the supervision of Dr. Manuel J. Maña López. The author was examined on 10th July 2014 by a committee formed by the doctors Manuel de Buenaga (European University of Madrid), Mariana Lara Neves (University of Berlin) and Jacinto Mata (University of Huelva). The PhD Thesis was awarded Summa cum laude (International Doctorate).
متن کاملClinical Abbreviation Disambiguation Using Neural Word Embeddings
This study examined the use of neural word embeddings for clinical abbreviation disambiguation, a special case of word sense disambiguation (WSD). We investigated three different methods for deriving word embeddings from a large unlabeled clinical corpus: one existing method called Surrounding based embedding feature (SBE), and two newly developed methods: Left-Right surrounding based embedding...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: VNU Journal of Science: Computer Science and Communication Engineering
سال: 2018
ISSN: 2588-1086,2615-9260
DOI: 10.25073/2588-1086/vnucsce.211