Current problems in diagnostic radiology
Oct 9, 2018
PURPOSE: To use a natural language processing and machine learning algorithm to evaluate inter-radiologist report variation and compare variation between radiologists using highly structured versus more free text reporting.
Beck's insight-that beliefs about one's self, future, and environment shape behavior-transformed depression treatment. Yet environment beliefs remain relatively understudied. We introduce a set of environment beliefs- or -that concern the world's ove...
Progress in reducing diagnostic errors remains slow partly due to poorly defined methods to identify errors, high-risk situations, and adverse events. Electronic trigger (e-trigger) tools, which mine vast amounts of patient data to identify signals i...
IMPORTANCE: To improve patient safety, health care systems need reliable methods to detect adverse events in large patient populations. Events are often described in clinical notes, rather than structured data, which make them difficult to identify o...
With the development of large-scale knowledge bases (KBs), knowledge-based question answering (KBQA) has become an important research topic in recent years. The key task in KBQA is relation detection, which is the process of finding a compatible answ...
The process of discovering novel drugs to treat diseases requires a long time and high cost. It is important to understand side effects of drugs as well as their therapeutic effects, because these can seriously damage the patients due to unexpected a...
Neural networks : the official journal of the International Neural Network Society
Sep 21, 2018
Exploiting graph-structured data has many real applications in domains including natural language semantics, programming language processing, and malware analysis. A variety of methods has been developed to deal with such data. However, learning grap...
BMC medical informatics and decision making
Sep 14, 2018
BACKGROUND: Clinical notes such as discharge summaries have a semi- or unstructured format. These documents contain information about diseases, treatments, drugs, etc. Extracting meaningful information from them becomes challenging due to their narra...
BACKGROUND: Word embeddings have been prevalently used in biomedical Natural Language Processing (NLP) applications due to the ability of the vector representations being able to capture useful semantic properties and linguistic relationships between...
BACKGROUND: Fulfilling the vision of Semantic Web requires an accurate data model for organizing knowledge and sharing common understanding of the domain. Fitting this description, ontologies are the cornerstones of Semantic Web and can be used to so...
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