Journal of the American Medical Informatics Association : JAMIA
Jul 1, 2020
OBJECTIVE: The goal of this study is to develop a robust Time Event Ontology (TEO), which can formally represent and reason both structured and unstructured temporal information.
Artificial intelligence generally and machine learning specifically have become deeply woven into the lives and technologies of modern life. Machine learning is dramatically changing scientific research and industry and may also hold promise for addr...
AIMS: Natural Language Processing (NLP) offers an automated method to extract data from unstructured free text fields for arthroplasty registry participation. Our objective was to investigate how accurately NLP can be used to extract structured clini...
Studies in health technology and informatics
Jun 26, 2020
The number of scientific publications is constantly growing to make their processing extremely time-consuming. We hypothesized that a user-defined literature tracking may be augmented by machine learning on article summaries. A specific dataset of 67...
Studies in health technology and informatics
Jun 26, 2020
Having precise information about health IT evaluation studies is important for evidence-based decisions in medical informatics. In a former feasibility study, we used a faceted search based on ontological modeling of key elements of studies to retrie...
Studies in health technology and informatics
Jun 26, 2020
The automated detection of adverse events in medical records might be a cost-effective solution for patient safety management or pharmacovigilance. Our group proposed an information extraction algorithm (IEA) for detecting adverse events in neurosurg...
Studies in health technology and informatics
Jun 16, 2020
Determining the cause of death of hospitalized patients with cardiovascular disease is of the utmost importance. This is usually recorded in free text form. In this study we aimed to develop a series of supervised natural language processing algorith...
Studies in health technology and informatics
Jun 16, 2020
Recent studies in the biomedical domain suggest that learning statistical word representations (static or contextualized word embeddings) on large corpora of specialized data improve the results on downstream natural language processing (NLP) tasks. ...
Studies in health technology and informatics
Jun 16, 2020
Parallel sentences provide semantically similar information which can vary on a given dimension, such as language or register. Parallel sentences with register variation (like expert and non-expert documents) can be exploited for the automatic text s...
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