A Revealed Imperfection in Concept Drift Correction in Metabolomics Modeling
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F22%3APU144947" target="_blank" >RIV/00216305:26220/22:PU144947 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-031-09135-3" target="_blank" >http://dx.doi.org/10.1007/978-3-031-09135-3</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-031-09135-3" target="_blank" >10.1007/978-3-031-09135-3</a>
Alternative languages
Result language
angličtina
Original language name
A Revealed Imperfection in Concept Drift Correction in Metabolomics Modeling
Original language description
Prediction models that rely on time series data are often affected by diminished predictive accuracy. This occurs from the causal relationships of the data that shift over time. Thus, the changing weights that are used to create prediction models lose their informational value. One way to correct this change is by using concept drift information. That is exactly what prediction models in biomedical applications need. Currently, metabolomics is at the forefront in modeling analysis for phenotype prediction, making it one of the most interesting candidates for biomedical prediction diagnosis. However, metabolomics datasets include dynamic information that can harm prediction modeling. The study presents concept drift correction methods to account for dynamic changes that occur in metabolomics data for better prediction outcomes of phenotypes in a biomedical setting.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/EF19_073%2F0016948" target="_blank" >EF19_073/0016948: Quality internal grants at BUT</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Information Technology in Biomedicine
ISBN
978-3-031-09135-3
ISSN
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e-ISSN
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Number of pages
12
Pages from-to
498-509
Publisher name
Springer
Place of publication
neuveden
Event location
Poland, Kamień Śląski
Event date
Jun 20, 2022
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
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