Phenotype classification of zebrafish embryos by supervised learning

PLoS ONE

Volumn 10, Issue 1, 2015, Pages

  Jeanray, Nathalie ^a   Marée, Raphaël ^a   Pruvot, Benoist ^a   Stern, Olivier ^a   Geurts, Pierre ^a   Wehenkel, Louis ^a   Muller, Marc ^a  

^a UNIVERSITY OF LIÈGE   (Belgium)

Author keywords

[No Author keywords available]

Indexed keywords

CHEMICAL COMPOUND; AMIODARONE; PROPRANOLOL;

ADULT; ANIMAL EXPERIMENT; ARTICLE; AUTOMATION; CONTROLLED STUDY; EMBRYO; EMBRYO DEVELOPMENT; FEMALE; IMAGE ANALYSIS; LARVA; LEARNING; MACHINE LEARNING; MALE; METHODOLOGY; NONHUMAN; PHENOTYPE; REPRODUCIBILITY; SURVIVAL; WILD TYPE; WORKLOAD; ZEBRA FISH; ANIMAL; DRUG EFFECTS; GROWTH, DEVELOPMENT AND AGING; IMAGE PROCESSING; NONMAMMALIAN EMBRYO; PHYSIOLOGY;

DANIO RERIO;

AMIODARONE; ANIMALS; AUTOMATION; EMBRYO, NONMAMMALIAN; IMAGE PROCESSING, COMPUTER-ASSISTED; LARVA; MACHINE LEARNING; PHENOTYPE; PROPRANOLOL; ZEBRAFISH;

EID: 84956623591     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0116989     Document Type: Article

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