Named entity recognition over electronic health records through a combined dictionary-based approach
AP Quimbaya, AS Múnera, RAG Rivera… - Procedia Computer …, 2016 - Elsevier
In health care information systems, electronic health records are an important part of the
knowledge concerning individual health histories. Extracting valuable knowledge from these …
knowledge concerning individual health histories. Extracting valuable knowledge from these …
[HTML][HTML] Use of “off-the-shelf” information extraction algorithms in clinical informatics: A feasibility study of MetaMap annotation of Italian medical notes
E Chiaramello, F Pinciroli, A Bonalumi, A Caroli… - Journal of biomedical …, 2016 - Elsevier
Abstract Information extraction from narrative clinical notes is useful for patient care, as well
as for secondary use of medical data, for research or clinical purposes. Many studies …
as for secondary use of medical data, for research or clinical purposes. Many studies …
A fine-grained corpus annotation schema of German nephrology records
In this work we present a fine-grained annotation schema to detect named entities in
German clinical data of chronically ill patients with kidney diseases. The annotation schema …
German clinical data of chronically ill patients with kidney diseases. The annotation schema …
Named entity recognition in swedish health records with character-based deep bidirectional lstms
S Almgren, S Pavlov, O Mogren - … of the Fifth Workshop on Building …, 2016 - aclanthology.org
We propose an approach for named entity recognition in medical data, using a character-
based deep bidirectional recurrent neural network. Such models can learn features and …
based deep bidirectional recurrent neural network. Such models can learn features and …
[PDF][PDF] Wrappers for Feature Subset Selection in CRF-based Clinical Information Extraction.
M Ebersbach, R Herms, C Lohr, M Eibl - CLEF (Working Notes), 2016 - academia.edu
We present our methodology and the results for Task 1 of the CLEF eHealth Evaluation Lab
2016. This benchmark addresses clinical information extraction related to nursing shift …
2016. This benchmark addresses clinical information extraction related to nursing shift …
Semi-Supervised Named Entity Recognition of Medical Entities in Swedish
S Almgren, S Pavlov - 2016 - odr.chalmers.se
A big opportunity within today's society is the vast amounts of data generated each day.
Especially within the health-care sector where a lot of journals are written daily and needs to …
Especially within the health-care sector where a lot of journals are written daily and needs to …
Similarity based Fuzzy and Possibilistic K-Means Clustering on Biomedical Data for Disease Evaluation
S Prema, P Umamaheswari - Asian Journal of Research in …, 2016 - indianjournals.com
The abundance amount of biomedical data availability has drastically increased the need for
new data mining techniques in order to obtain the health related information. To identify and …
new data mining techniques in order to obtain the health related information. To identify and …
[PDF][PDF] Named entity recognition in unstructured text.
S Keretna - 2016 - dro.deakin.edu.au
Named entity recognition in unstructured text. Page 1 Named entity recognition in
unstructured text. AUTHOR(S) Nikos Pandis PUBLICATION DATE 01-06-2016 HANDLE …
unstructured text. AUTHOR(S) Nikos Pandis PUBLICATION DATE 01-06-2016 HANDLE …