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Information Storage and Retrieval

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A mobile health monitoring-and-treatment system based on integration of the SSN sensor ontology and the HL7 FHIR standard.

BMC medical informatics and decision making
BACKGROUND: Mobile health (MH) technologies including clinical decision support systems (CDSS) provide an efficient method for patient monitoring and treatment. A mobile CDSS is based on real-time sensor data and historical electronic health record (...

Deep Belief CNN Feature Representation Based Content Based Image Retrieval for Medical Images.

Journal of medical systems
Avascular Necrosis (AN) is a cause of muscular-skeletal disability. As it is common amongst the younger people, early intervention and prompt diagnosis is requisite. This disease normally affects the femoral bones, in order that the bones' shape gets...

BoSR: A CNN-based aurora image retrieval method.

Neural networks : the official journal of the International Neural Network Society
The deep learning models especially the CNN have achieved amazing performance on natural image retrieval. However, remote sensing images captured with anamorphic lens are still retrieved via manual selection or traditional SIFT-based methods. How to ...

Open access image repositories: high-quality data to enable machine learning research.

Clinical radiology
Originally motivated by the need for research reproducibility and data reuse, large-scale, open access information repositories have become key resources for training and testing of advanced machine learning applications in biomedical and clinical re...

[Can Big Data change our practices?].

Journal francais d'ophtalmologie
The European Medicines Agency has defined Big Data by the "3 V's": Volume, Velocity and Variety. These large databases allow access to real life data on patient care. They are particularly suited for studies of adverse events and pharmacoepidemiology...

A deep learning model incorporating part of speech and self-matching attention for named entity recognition of Chinese electronic medical records.

BMC medical informatics and decision making
BACKGROUND: The Named Entity Recognition (NER) task as a key step in the extraction of health information, has encountered many challenges in Chinese Electronic Medical Records (EMRs). Firstly, the casual use of Chinese abbreviations and doctors' per...

A fine-grained Chinese word segmentation and part-of-speech tagging corpus for clinical text.

BMC medical informatics and decision making
BACKGROUND: Chinese word segmentation (CWS) and part-of-speech (POS) tagging are two fundamental tasks of Chinese text processing. They are usually preliminary steps for lots of Chinese natural language processing (NLP) tasks. There have been a large...

A hybrid approach for named entity recognition in Chinese electronic medical record.

BMC medical informatics and decision making
BACKGROUND: With the rapid spread of electronic medical records and the arrival of medical big data era, the application of natural language processing technology in biomedicine has become a hot research topic.

On building a diabetes centric knowledge base via mining the web.

BMC medical informatics and decision making
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
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...