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Statements

Subject Item
n2:RIV%2F68407700%3A21230%2F03%3A00087920%21RIV10-MSM-21230___
rdf:type
n10:Vysledek skos:Concept
dcterms:description
Data collected in medical experiments are most often carefully analysed using statistical SW packages. These SW packages have become a standard equipment of any laboratory collecting experimental data. We argue that it is time to enhance this equipment by machine learning methods which have been designed and developed during the last twenty years. We present a case study which proves that machine learning algorithms can serve as a valuable source of heuristics when searching for interesting hypotheses, which are valid in the collected data. Data collected in medical experiments are most often carefully analysed using statistical SW packages. These SW packages have become a standard equipment of any laboratory collecting experimental data. We argue that it is time to enhance this equipment by machine learning methods which have been designed and developed during the last twenty years. We present a case study which proves that machine learning algorithms can serve as a valuable source of heuristics when searching for interesting hypotheses, which are valid in the collected data.
dcterms:title
Formation of Hypotheses on Stress Using Machine Learning Methods Formation of Hypotheses on Stress Using Machine Learning Methods
skos:prefLabel
Formation of Hypotheses on Stress Using Machine Learning Methods Formation of Hypotheses on Stress Using Machine Learning Methods
skos:notation
RIV/68407700:21230/03:00087920!RIV10-MSM-21230___
n4:aktivita
n7:R
n4:aktivity
R
n4:dodaniDat
n12:2010
n4:domaciTvurceVysledku
n13:5112605 n13:9942904
n4:druhVysledku
n18:D
n4:duvernostUdaju
n14:S
n4:entitaPredkladatele
n8:predkladatel
n4:idSjednocenehoVysledku
607583
n4:idVysledku
RIV/68407700:21230/03:00087920
n4:jazykVysledku
n19:eng
n4:klicovaSlova
medical experiments; machine learning
n4:klicoveSlovo
n5:medical%20experiments n5:machine%20learning
n4:kontrolniKodProRIV
[77C670A8DDE4]
n4:mistoKonaniAkce
Praha
n4:mistoVydani
Praha
n4:nazevZdroje
Intelligent and Adaptive Systems in Medicine
n4:obor
n16:JC
n4:pocetDomacichTvurcuVysledku
2
n4:pocetTvurcuVysledku
4
n4:rokUplatneniVysledku
n12:2003
n4:tvurceVysledku
Nováková, Lenka Štěpánková, Olga
n4:typAkce
n9:EUR
n4:zahajeniAkce
2003-03-31+02:00
s:issn
1213-3000
s:numberOfPages
6
n11:hasPublisher
České vysoké učení technické v Praze. Fakulta elektrotechnická
n17:organizacniJednotka
21230