AIMC Topic: Information Storage and Retrieval
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A Study of Concept Extraction Across Different Types of Clinical Notes.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Nov 5, 2015
Our research investigates methods for creating effective concept extractors for specialty clinical notes. First, we present three new "specialty area" datasets consisting of Cardiology, Neurology, and Orthopedics clinical notes manually annotated wit...
An Ensemble Method for Spelling Correction in Consumer Health Questions.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Nov 5, 2015
Orthographic and grammatical errors are a common feature of informal texts written by lay people. Health-related questions asked by consumers are a case in point. Automatic interpretation of consumer health questions is hampered by such errors. In th...
POETenceph - Automatic identification of clinical notes indicating encephalopathy using a realist ontology.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Nov 5, 2015
Identifying inpatients with encephalopathy is important. The disorder is prevalent, often missed, and puts patients at risk. We describe POETenceph, natural language processing pipeline, which ranks clinical notes on the extent to which they indicate...
COHeRE: Cross-Ontology Hierarchical Relation Examination for Ontology Quality Assurance.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Nov 5, 2015
Biomedical ontologies play a vital role in healthcare information management, data integration, and decision support. Ontology quality assurance (OQA) is an indispensable part of the ontology engineering cycle. Most existing OQA methods are based on ...
Characterization of the Context of Drug Concepts in Research Protocols: An Empiric Study to Guide Ontology Development.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Nov 5, 2015
We examined a large body of research study documents (protocols) to identify mentions of drug concepts and established base concepts and roles needed to characterize the semantics of these instances. We found these concepts in three general situation...
A novel fuzzy logic-based image steganography method to ensure medical data security.
Computers in biology and medicine
Oct 27, 2015
This study aims to secure medical data by combining them into one file format using steganographic methods. The electroencephalogram (EEG) is selected as hidden data, and magnetic resonance (MR) images are also used as the cover image. In addition to...
Practical applications for natural language processing in clinical research: The 2014 i2b2/UTHealth shared tasks.
Journal of biomedical informatics
Oct 24, 2015
[Comparison of ICD 10 and AIS with the Development of a Method for Automated Conversion].
Zeitschrift fur Orthopadie und Unfallchirurgie
Oct 15, 2015
BACKGROUND: Most of the current scores and outcome prediction calculations in traumatology are based on the Abbreviated Injury Scale (AIS). However, this is not routinely used for documentation and coding of injuries in many countries, including Germ...
Building integrated ontological knowledge structures with efficient approximation algorithms.
BioMed research international
Oct 13, 2015
The integration of ontologies builds knowledge structures which brings new understanding on existing terminologies and their associations. With the steady increase in the number of ontologies, automatic integration of ontologies is preferable over ma...
Information extraction from multi-institutional radiology reports.
Artificial intelligence in medicine
Oct 3, 2015
OBJECTIVES: The radiology report is the most important source of clinical imaging information. It documents critical information about the patient's health and the radiologist's interpretation of medical findings. It also communicates information to ...
Humans
Radiology Information Systems
Medical Record Linkage
Information Storage and Retrieval
Semantics
Pattern Recognition, Automated
Predictive Value of Tests
Natural Language Processing
Discriminant Analysis
Radiographic Image Interpretation, Computer-Assisted
Data Mining
Observer Variation
Reproducibility of Results
Machine Learning
United States
Databases, Factual
Models, Theoretical
Electronic Health Records
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