Innovative statistical approaches: the use of neural networks reduces the sample size in the splenectomy-MCAO mouse model.

Journal: Croatian medical journal

PMID: 38706238

Abstract

AIM: To compare the effectiveness of artificial neural network (ANN) and traditional statistical analysis on identical data sets within the splenectomy-middle carotid artery occlusion (MCAO) mouse model.

Authors

Dominik Romić

Department of Neurosurgery, University Hospital Dubrava, Zagreb, Croatia.
Monika Berecki
Sanja Srakočić
Paula Josić Dominović
Helena Justić
Dominik Hamer
Daniela Petrinec
Marina Radmilović
Branimir Hackenberger
Srećko Gajović

Srećko Gajović, University of Zagreb School of Medicine, Croatian Institute for Brain Research, Zagreb, Croatia, srecko.gajovic@hiim.hr.
Anton Glasnović

Anton Glasnović, Croatian Institute for Brain Research, University of Zagreb School of Medicine, Šalata 12, 10000 Zagreb, Croatia, anton.glasnovic@mef.hr.

Keywords

Animals Disease Models, Animal Infarction, Middle Cerebral Artery Magnetic Resonance Imaging Male Mice Neural Networks, Computer Sample Size Splenectomy

External Resources

View on PubMed Access via DOI PubMed (38706238)

Innovative statistical approaches: the use of neural networks reduces the sample size in the splenectomy-MCAO mouse model.

Abstract

Authors

Keywords

External Resources

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