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Predicting chemicals' toxicity pathway of female reproductive disorders using AOP7 and deep neural networks
| Naziv: | Predicting chemicals' toxicity pathway of female reproductive disorders using AOP7 and deep neural networks | Autori: | Sukur Nataša   ; Milošević Nemanja ; Pogrmić-Majkić Kristina ; Stanić Bojana ; Andrić Nebojša |
Godina: | 2023 | Publikacija: | Food and Chemical Toxicology | ISSN: | 0278-6915 Food and Chemical Toxicology Pretraži identifikator |
Tip rezultata: | Naučni članak | Kolacija: | 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-kategorija: | 21aM21a - Vodeći međunarodni časopis kategorije M21a |
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