Ant-inspired Algorithms in Health Information System Data Mining, Classification and Visualization

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21460%2F16%3A00307020" target="_blank" >RIV/68407700:21460/16:00307020 - isvavai.cz</a>

Alternative codes found

RIV/68407700:21730/16:00307020

Result on the web

<a href="http://80.link.springer.com.dialog.cvut.cz/chapter/10.1007/978-3-319-32703-7_171" target="_blank" >http://80.link.springer.com.dialog.cvut.cz/chapter/10.1007/978-3-319-32703-7_171</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-32703-7_170" target="_blank" >10.1007/978-3-319-32703-7_170</a>

Result language

angličtina

Original language name

Ant-inspired Algorithms in Health Information System Data Mining, Classification and Visualization

Original language description

In the paper we describe the process of cardiotocography (CTG) record clustering and the effort that was taken to retrieve information from an old (approx. 15 yrs) hospital information system. It consisted of retrieving data from DB tables in the form of unstructured text attributes. Information retrieval had to be performed for complementing cardiotocography signals with additional information. This was needed for further rule discovery mining and automated processing as the main goal was asphyxia prediction during delivery. A graph-based visualization technique has been designed and developed. Together with experts it helped to handle and efficiently process great amount of unstructured (or semi-structured data). Of course, we have used and tested several approaches: automated, semi-automated and manual clustering of the records. In the (semi-)automated experiments we have used k-means, self-organizing map and self-organizing approach inspired by ant-colonies. The overview obtained was consulted with medical experts and served for further mining and information retrieval from the database. Furthermore, an evaluation of CTG signal classification was carried out using multiple methods. These methods used different classification approaches (Naive Bayes, rule and tree based classifiers, etc.). We conducted ten-fold crossvalidation and for each experiment we have gathered multiple quantitative objective measures that have been statistically evaluated. As the best-performing method we have identified the ant-inspired ACO_DTree algorithm that performed significantly better and provided comprehensible results.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

JD - Use of computers, robotics and its application

OECD FORD branch

—

Project

<a href="/en/project/NV15-31398A" target="_blank" >NV15-31398A: Features of Electromechanical Dyssynchrony that Predict Effect of Cardiac Resynchronization Therapy</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2016

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

XIV MEDITERRANEAN CONFERENCE ON MEDICAL AND BIOLOGICAL ENGINEERING AND COMPUTING 2016

ISBN

978-3-319-32701-3

ISSN

1680-0737

e-ISSN

—

Number of pages

6

Pages from-to

868-873

Publisher name

Springer

Place of publication

New York

Event location

Paphos

Event date

Mar 31, 2016

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

000376283000170