[HTML][HTML] Recurrent neural networks for classifying relations in clinical notes
Y Luo - Journal of biomedical informatics, 2017 - Elsevier
We proposed the first models based on recurrent neural networks (more specifically Long
Short-Term Memory-LSTM) for classifying relations from clinical notes. We tested our models …
Short-Term Memory-LSTM) for classifying relations from clinical notes. We tested our models …
[ΒΙΒΛΙΟ][B] Deep learning techniques for biomedical and health informatics
Biomedical and Health Informatics is an emerging field of research at the intersection of
information science, computer science, and health care. Health care informatics and …
information science, computer science, and health care. Health care informatics and …
A new iterative method to reduce workload in systematic review process
High cost for systematic review of biomedical literature has generated interest in decreasing
overall workload. This can be done by applying natural language processing techniques to …
overall workload. This can be done by applying natural language processing techniques to …
[ΒΙΒΛΙΟ][B] Healthcare data analytics
CK Reddy, CC Aggarwal - 2015 - books.google.com
Supplying a comprehensive overview of healthcare analytics research, Healthcare Data
Analytics provides an understanding of the analytical techniques currently available to solve …
Analytics provides an understanding of the analytical techniques currently available to solve …
Combining unsupervised, supervised and rule-based learning: the case of detecting patient allergies in electronic health records
Background Data mining of electronic health records (EHRs) has a huge potential for
improving clinical decision support and to help healthcare deliver precision medicine …
improving clinical decision support and to help healthcare deliver precision medicine …
[PDF][PDF] 电子病历命名实体识别和实体关系抽取研究综述
杨锦锋， 于秋滨， 关毅， 蒋志鹏 - 自动化学报, 2014 - researchgate.net
摘要电子病历(Electronic medical records, EMR) 产生于临床治疗过程, 其中命名实体和实体
关系反映了患者健康状况, 包含了大量与患者健康状况密切相关的医疗知识 …
关系反映了患者健康状况, 包含了大量与患者健康状况密切相关的医疗知识 …
Clinical concept extraction with contextual word embedding
Automatic extraction of clinical concepts is an essential step for turning the unstructured data
within a clinical note into structured and actionable information. In this work, we propose a …
within a clinical note into structured and actionable information. In this work, we propose a …
Bidirectional LSTM-CRF for clinical concept extraction
Automated extraction of concepts from patient clinical records is an essential facilitator of
clinical research. For this reason, the 2010 i2b2/VA Natural Language Processing …
clinical research. For this reason, the 2010 i2b2/VA Natural Language Processing …
Fault diagnosis based on SPBO-SDAE and transformer neural network for rotating machinery
X Du, L Jia, IU Haq - Measurement, 2022 - Elsevier
Fault diagnosis for rotating machinery requires both high diagnosis accuracy and time
efficiency. A rotating machinery fault diagnosis method based on intelligent feature self …
efficiency. A rotating machinery fault diagnosis method based on intelligent feature self …
Machine learning-driven clinical decision support system for concept-based searching: a field trial in a Norwegian hospital
Background Natural language processing (NLP) based clinical decision support systems
(CDSSs) have demonstrated the ability to extract vital information from patient electronic …
(CDSSs) have demonstrated the ability to extract vital information from patient electronic …