AIMC Topic: Electronic Health Records
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On building a diabetes centric knowledge base via mining the web.
BMC medical informatics and decision making
Apr 9, 2019
BACKGROUND: Diabetes has become one of the hot topics in life science researches. To support the analytical procedures, researchers and analysts expend a mass of labor cost to collect experimental data, which is also error-prone. To reduce the cost a...
Attention-based deep residual learning network for entity relation extraction in Chinese EMRs.
BMC medical informatics and decision making
Apr 9, 2019
BACKGROUND: Electronic medical records (EMRs) contain a variety of valuable medical concepts and relations. The ability to recognize relations between medical concepts described in EMRs enables the automatic processing of clinical texts, resulting in...
Time-sensitive clinical concept embeddings learned from large electronic health records.
BMC medical informatics and decision making
Apr 9, 2019
BACKGROUND: Learning distributional representation of clinical concepts (e.g., diseases, drugs, and labs) is an important research area of deep learning in the medical domain. However, many existing relevant methods do not consider temporal dependenc...
Developing neural network models for early detection of cardiac arrest in emergency department.
The American journal of emergency medicine
Apr 7, 2019
BACKGROUND: Automated surveillance for cardiac arrests would be useful in overcrowded emergency departments. The purpose of this study is to develop and test artificial neural network (ANN) classifiers for early detection of patients at risk of cardi...
A hybrid neural network model for predicting kidney disease in hypertension patients based on electronic health records.
BMC medical informatics and decision making
Apr 4, 2019
BACKGROUND: Disease prediction based on Electronic Health Records (EHR) has become one hot research topic in biomedical community. Existing work mainly focuses on the prediction of one target disease, and little work is proposed for multiple associat...
Complexities, variations, and errors of numbering within clinical notes: the potential impact on information extraction and cohort-identification.
BMC medical informatics and decision making
Apr 4, 2019
BACKGROUND: Numbers and numerical concepts appear frequently in free text clinical notes from electronic health records. Knowledge of the frequent lexical variations of these numerical concepts, and their accurate identification, is important for man...
Developing a portable natural language processing based phenotyping system.
BMC medical informatics and decision making
Apr 4, 2019
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
Apr 4, 2019
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...
Natural language processing of radiology reports for identification of skeletal site-specific fractures.
BMC medical informatics and decision making
Apr 4, 2019
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...
Automated feature selection of predictors in electronic medical records data.
Biometrics
Apr 2, 2019
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...
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