loading
Papers

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Ioana Barbantan and Rodica Potolea

Affiliation: Technical University of Cluj-Napoca, Romania

ISBN: 978-989-758-203-5

Keyword(s): Data Mining, Classification, Value Mapping, Concept Extraction, Semantic Medical Data Alignment.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; BioInformatics & Pattern Discovery ; Computational Intelligence ; Concept Mining ; Evolutionary Computing ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Machine Learning ; Soft Computing ; Symbolic Systems

Abstract: In the attempt to build a complete solution for a medical assistive decision support system we proposed a complex flow that integrates a sequence of modules which target the different data engineering tasks. This solution can analyse any type of unstructured medical documents which are processed by applying specific NLP steps followed by semantic analysis which leads to the medical concepts identification, thus imposing a structure on the input documents. The data collection, document pre-processing, concept extraction, and correlation are modules that have been researched by us in our previous works and for which we proposed original solutions. Using the collected and structured representation of the medical records, informed decisions regarding the health status of the patients can be made. The current paper focuses on the prediction module that joins all the components in a logical flow and is completed with the suggested diagnosis classification for the patient. The accuracy rate of 81.25%, obtained on the medical documents supports the strength of our proposed strategy. (More)

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.231.229.89

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Barbantan, I. and Potolea, R. (2016). Learning Diagnosis from Electronic Health Records.In Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, (IC3K 2016) ISBN 978-989-758-203-5, pages 344-351. DOI: 10.5220/0006069503440351

@conference{kdir16,
author={Ioana Barbantan. and Rodica Potolea.},
title={Learning Diagnosis from Electronic Health Records},
booktitle={Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, (IC3K 2016)},
year={2016},
pages={344-351},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006069503440351},
isbn={978-989-758-203-5},
}

TY - CONF

JO - Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, (IC3K 2016)
TI - Learning Diagnosis from Electronic Health Records
SN - 978-989-758-203-5
AU - Barbantan, I.
AU - Potolea, R.
PY - 2016
SP - 344
EP - 351
DO - 10.5220/0006069503440351

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.