Mining the Strongest Patterns in Medical Sequential Data

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F05%3A03113280" target="_blank" >RIV/68407700:21230/05:03113280 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Mining the Strongest Patterns in Medical Sequential Data

Original language description

Sequential data represent an important source of automatically mined and potentially new medical knowledge. They can originate in various ways. Within the presented domain they come from a longitudinal preventive study of atherosclerosis - the data consist of series of long-term observations recording the development of risk factors and associated conditions. The intention is to identify frequent sequential patterns having any relation to an onset of any of the observed cardiovascular diseases. This paper focuses on application of inductive logic programming. The prospective patterns are based on first-order features automatically extracted from the sequential data. The features are further grouped in order to reach final complex patterns expressed asrules. The presented approach is also compared with the approaches published earlier (windowing, episode rules).

Czech name

Není k dispozici

Czech description

Není k dispozici

Type

A - Audiovisual production

CEP classification

JC - Computer hardware and software

OECD FORD branch

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Project

<a href="/en/project/KJB201210501" target="_blank" >KJB201210501: Logic-based machine learning for genomic data analysis</a><br>

Continuities

Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year

2005

Confidentiality

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

ISBN

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Place of publication

Praha

Publisher/client name

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Version

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Carrier ID

neuvedeno