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eNauka >  Results >  Predicting chemicals' toxicity pathway of female reproductive disorders using AOP7 and deep neural networks
Title: Predicting chemicals' toxicity pathway of female reproductive disorders using AOP7 and deep neural networks
Authors: Sukur Nataša  ; Milošević Nemanja  ; Pogrmić-Majkić Kristina  ; Stanić Bojana  ; Andrić Nebojša  
Issue Date: 2023
Publication: Food and Chemical Toxicology
ISSN: 0278-6915 Food and Chemical Toxicology Search Idenfier
Type: Article
Collation: vol. 180 str. 114013-114013
DOI: 10.1016/j.fct.2023.114013
WoS-ID: 001082451700001
Scopus-ID: 2-s2.0-85170690219
URI: https://cris.uns.ac.rs/en/scientific-results/journal-publication/46879
https://www.cris.uns.ac.rs/record.jsf?recordId=133183&source=eNauka&language=en
https://enauka.gov.rs/handle/123456789/786685
M-category: 
21aM21a

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