ArticleJournal of biomedical informatics2016
Speculation detection for Chinese clinical notes: Impacts of word segmentation and embedding models.
Article in Journal of biomedical informatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Large language model ensemble for automated TNM staging from radiology reports.Bioinformatics (Oxford, England) · 2026Article
- Multimodal models for skin cancer classification using clinical freetext and dermatoscopic images.Communications medicine · 2026Article
- A framework for normalized extraction of fine-grained traditional Chinese medicine symptom entities and relations.BMC medical informatics and decision making · 2025Article
- Creating an ignorance-base: Exploring known unknowns in the scientific literature.Journal of biomedical informatics · 2023Article
- Construction of an Assisted Model Based on Natural Language Processing for Automatic Early Diagnosis of Autoimmune Encephalitis.Neurology and therapy · 2022Article
- Negation and uncertainty detection in clinical texts written in Spanish: a deep learning-based approach.PeerJ. Computer science · 2022Article
- Constructing fine-grained entity recognition corpora based on clinical records of traditional Chinese medicine.BMC medical informatics and decision making · 2020Article
- Feature extraction for phenotyping from semantic and knowledge resources.Journal of biomedical informatics · 2019Article
- Mining and standardizing chinese consumer health terms.BMC medical informatics and decision making · 2018Article
- Clinical Natural Language Processing in languages other than English: opportunities and challenges.Journal of biomedical semantics · 2018Review
- EliIE: An open-source information extraction system for clinical trial eligibility criteria.Journal of the American Medical Informatics Association : JAMIA · 2017Article
- A cascaded approach for Chinese clinical text de-identification with less annotation effort.Journal of biomedical informatics · 2017Article
- Making Sense of Big Textual Data for Health Care: Findings from the Section on Clinical Natural Language Processing.Yearbook of medical informatics · 2017Review
- Classifying Chinese Questions Related to Health Care Posted by Consumers Via the Internet.Journal of medical Internet research · 2017Article
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6 authors.
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Abstract
Speculations represent uncertainty toward certain facts. In clinical texts, identifying speculations is a critical step of natural language processing (NLP). While it is a nontrivial task in many languages, detecting speculations in Chinese clinical notes can be particularly challenging because word segmentation may be necessary as an upstream operation. The objective of this paper is to construct a state-of-the-art speculation detection system for Chinese clinical notes and to investigate whether embedding features and word segmentations are worth exploiting toward this overall task. We propose a sequence labeling based system for speculation detection, which relies on features from bag of characters, bag of words, character embedding, and word embedding. We experiment on a novel dataset of 36,828 clinical notes with 5103 gold-standard speculation annotations on 2000 notes, and compare the systems in which word embeddings are calculated based on word segmentations given by general and by domain specific segmenters respectively. Our systems are able to reach performance as high as 92.2% measured by F score. We demonstrate that word segmentation is critical to produce high quality word embedding to facilitate downstream information extraction applications, and suggest that a domain dependent word segmenter can be vital to such a clinical NLP task in Chinese language.
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