AIMC Topic: Natural Language Processing

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Developing a portable natural language processing based phenotyping system.

BMC medical informatics and decision making
BACKGROUND: This paper presents a portable phenotyping system that is capable of integrating both rule-based and statistical machine learning based approaches.

Entity recognition in Chinese clinical text using attention-based CNN-LSTM-CRF.

BMC medical informatics and decision making
BACKGROUND: Clinical entity recognition as a fundamental task of clinical text processing has been attracted a great deal of attention during the last decade. However, most studies focus on clinical text in English rather than other languages. Recent...

A two-site survey of medical center personnel's willingness to share clinical data for research: implications for reproducible health NLP research.

BMC medical informatics and decision making
BACKGROUND: A shareable repository of clinical notes is critical for advancing natural language processing (NLP) research, and therefore a goal of many NLP researchers is to create a shareable repository of clinical notes, that has breadth (from mult...

Clinical text classification with rule-based features and knowledge-guided convolutional neural networks.

BMC medical informatics and decision making
BACKGROUND: Clinical text classification is an fundamental problem in medical natural language processing. Existing studies have cocnventionally focused on rules or knowledge sources-based feature engineering, but only a limited number of studies hav...

Parsing clinical text using the state-of-the-art deep learning based parsers: a systematic comparison.

BMC medical informatics and decision making
BACKGROUND: A shareable repository of clinical notes is critical for advancing natural language processing (NLP) research, and therefore a goal of many NLP researchers is to create a shareable repository of clinical notes, that has breadth (from mult...

Extracting health-related causality from twitter messages using natural language processing.

BMC medical informatics and decision making
BACKGROUND: Twitter messages (tweets) contain various types of topics in our daily life, which include health-related topics. Analysis of health-related tweets would help us understand health conditions and concerns encountered in our daily lives. In...

Natural language processing of radiology reports for identification of skeletal site-specific fractures.

BMC medical informatics and decision making
BACKGROUND: Osteoporosis has become an important public health issue. Most of the population, particularly elderly people, are at some degree of risk of osteoporosis-related fractures. Accurate identification and surveillance of patient populations w...

Natural Language Statistical Features of LSTM-Generated Texts.

IEEE transactions on neural networks and learning systems
Long short-term memory (LSTM) networks have recently shown remarkable performance in several tasks that are dealing with natural language generation, such as image captioning or poetry composition. Yet, only few works have analyzed text generated by ...

Automated feature selection of predictors in electronic medical records data.

Biometrics
The use of Electronic Health Records (EHR) for translational research can be challenging due to difficulty in extracting accurate disease phenotype data. Historically, EHR algorithms for annotating phenotypes have been either rule-based or trained wi...