A Machine-learning Approach to Survival Time-event Predicting: Initial Analyses using Stomach Cancer Data
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61384399%3A31140%2F20%3A00056144" target="_blank" >RIV/61384399:31140/20:00056144 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/9280301" target="_blank" >https://ieeexplore.ieee.org/document/9280301</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/EHB50910.2020.9280301" target="_blank" >10.1109/EHB50910.2020.9280301</a>
Alternative languages
Result language
angličtina
Original language name
A Machine-learning Approach to Survival Time-event Predicting: Initial Analyses using Stomach Cancer Data
Original language description
Main topics of the document: survival analysis; machine-learning; time-event prediction; time-event; variable decomposition; Cox proportional hazard model
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10101 - Pure mathematics
Result continuities
Project
—
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2020 International Conference on e-Health and Bioengineering (EHB)
ISBN
978-1-7281-8804-1
ISSN
2575-5145
e-ISSN
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Number of pages
4
Pages from-to
1-4
Publisher name
IEEE
Place of publication
USA
Event location
Iasi
Event date
Oct 29, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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