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Title: Improving interpretability: combined use of LVQ and ARTMAP in decision support, Journal of Telecommunications and Information Technology, 2005,nr 4

Creator:

Raffone, Antonino ; Giorgi, Andrea ; Kwok, Hoi Fei

Date:

2005, nr 4

Resource Type:

artykuł

Description:

The learning vector quantization (LVQ) network was used to classify the ECG ST segment into different morphological categories. Due to the lack of data in the ST elevation categories, the classifier was only trained to identify different types of ST depressions (horizontal, upsloping and downsloping). The accuracies were 91%, 85% and 65% respectively for the training, validation and testing data respectively. Despite the low accuracy for the testing data, most of the mis-classifications were downsloping ST depression being classified as horizontal ST depression. We concluded that more data and more training are needed in order to train the LVQ to recognize other morphological types of ST deviation and to improve the accuracy.

Publisher:

Instytut Łączności - Państwowy Instytut Badawczy, Warszawa

Format:

application/pdf

Resource Identifier:

oai:bc.itl.waw.pl:502

DOI:

10.26636/jtit.2005.4.336

ISSN:

1509-4553

eISSN:

1899-8852

Source:

Journal of Telecommunications and Information Technology

Language:

ang

Rights Management:

Biblioteka Naukowa Instytutu Łączności

Subject and keywords:

decision support systems ischemic heart disease learning vector quantization ARTMAP

Object collections:

Last modified:

Jun 19, 2024

In our library since:

Mar 9, 2010

Number of object content hits:

326

All available object's versions:

https://bc.itl.waw.pl/publication/561

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Edition name Date
Kwok, Hoi Fei; Giorgi, Andrea; Raffone, Antonino, Improving interpretability: combined use of LVQ and ARTMAP in decision support, Journal of Telecommunications and Information Technology, 2005,nr 4 Jun 19, 2024

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E-Mail

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