AIMC Journal:
Journal of biomedical informatics

Showing 501 to 510 of 650 articles

Automatic prediction of coronary artery disease from clinical narratives.

Journal of biomedical informatics Jun 27, 2017
Coronary Artery Disease (CAD) is not only the most common form of heart disease, but also the leading cause of death in both men and women (Coronary Artery Disease: MedlinePlus, 2015). We present a system that is able to automatically predict whether...
Forecasting Prognosis Female Male Humans Vocabulary, Controlled Narration Natural Language Processing Coronary Artery Disease
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DrugSemantics: A corpus for Named Entity Recognition in Spanish Summaries of Product Characteristics.

Journal of biomedical informatics Jun 15, 2017
For the healthcare sector, it is critical to exploit the vast amount of textual health-related information. Nevertheless, healthcare providers have difficulties to benefit from such quantity of data during pharmacotherapeutic care. The problem is tha...
Semantics Drug Labeling Natural Language Processing Humans Language Reproducibility of Results
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Predicting mental conditions based on "history of present illness" in psychiatric notes with deep neural networks.

Journal of biomedical informatics Jun 10, 2017
BACKGROUND: Applications of natural language processing to mental health notes are not common given the sensitive nature of the associated narratives. The CEGS N-GRID 2016 Shared Task in Clinical Natural Language Processing (NLP) changed this scenari...
Humans Mental Disorders Natural Language Processing Neural Networks, Computer Machine Learning
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A deep learning approach for predicting the quality of online health expert question-answering services.

Journal of biomedical informatics Jun 9, 2017
Recently, online health expert question-answering (HQA) services (systems) have attracted more and more health consumers to ask health-related questions everywhere at any time due to the convenience and effectiveness. However, the quality of answers ...
Consumer Health Information Semantics Humans Machine Learning Delivery of Health Care Quality Control
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A hybrid approach to automatic de-identification of psychiatric notes.

Journal of biomedical informatics Jun 7, 2017
De-identification, or identifying and removing protected health information (PHI) from clinical data, is a critical step in making clinical data available for clinical applications and research. This paper presents a natural language processing syste...
Data Anonymization Mental Disorders Humans Automation Natural Language Processing
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An empirical analysis of ontology reuse in BioPortal.

Journal of biomedical informatics Jun 2, 2017
Biomedical ontologies often reuse content (i.e., classes and properties) from other ontologies. Content reuse enables a consistent representation of a domain and reusing content can save an ontology author significant time and effort. Prior studies h...
Software Biological Ontologies Quality Control Vocabulary, Controlled
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De-identification of clinical notes via recurrent neural network and conditional random field.

Journal of biomedical informatics Jun 1, 2017
De-identification, identifying information from data, such as protected health information (PHI) present in clinical data, is a critical step to enable data to be shared or published. The 2016 Centers of Excellence in Genomic Science (CEGS) Neuropsyc...
Humans Neural Networks, Computer Natural Language Processing Health Insurance Portability and Accountability Act Electronic Health Records United States
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RysannMD: A biomedical semantic annotator balancing speed and accuracy.

Journal of biomedical informatics May 26, 2017
Recently, both researchers and practitioners have explored the possibility of semantically annotating large and continuously evolving collections of biomedical texts such as research papers, medical reports, and physician notes in order to enable the...
Semantics Natural Language Processing Humans Data Curation Data Mining
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Semi-supervised medical entity recognition: A study on Spanish and Swedish clinical corpora.

Journal of biomedical informatics May 16, 2017
OBJECTIVE: The goal of this study is to investigate entity recognition within Electronic Health Records (EHRs) focusing on Spanish and Swedish. Of particular importance is a robust representation of the entities. In our case, we utilized unsupervised...
Sweden Cluster Analysis Electronic Health Records Humans Semantics Machine Learning Data Curation
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Ordinal convolutional neural networks for predicting RDoC positive valence psychiatric symptom severity scores.

Journal of biomedical informatics May 12, 2017
BACKGROUND: The CEGS N-GRID 2016 Shared Task in Clinical Natural Language Processing (NLP) provided a set of 1000 neuropsychiatric notes to participants as part of a competition to predict psychiatric symptom severity scores. This paper summarizes ou...
Humans Neural Networks, Computer Neuropsychological Tests Severity of Illness Index
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