تقرير
Launching into clinical space with medspaCy: a new clinical text processing toolkit in Python
العنوان: | Launching into clinical space with medspaCy: a new clinical text processing toolkit in Python |
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المؤلفون: | Eyre, Hannah, Chapman, Alec B, Peterson, Kelly S, Shi, Jianlin, Alba, Patrick R, Jones, Makoto M, Box, Tamara L, DuVall, Scott L, Patterson, Olga V |
سنة النشر: | 2021 |
المجموعة: | Computer Science |
مصطلحات موضوعية: | Computer Science - Computation and Language |
الوصف: | Despite impressive success of machine learning algorithms in clinical natural language processing (cNLP), rule-based approaches still have a prominent role. In this paper, we introduce medspaCy, an extensible, open-source cNLP library based on spaCy framework that allows flexible integration of rule-based and machine learning-based algorithms adapted to clinical text. MedspaCy includes a variety of components that meet common cNLP needs such as context analysis and mapping to standard terminologies. By utilizing spaCy's clear and easy-to-use conventions, medspaCy enables development of custom pipelines that integrate easily with other spaCy-based modules. Our toolkit includes several core components and facilitates rapid development of pipelines for clinical text. Comment: Accepted to AMIA Annual Symposium 2021 |
نوع الوثيقة: | Working Paper |
URL الوصول: | http://arxiv.org/abs/2106.07799 |
رقم الأكسشن: | edsarx.2106.07799 |
قاعدة البيانات: | arXiv |
الوصف غير متاح. |