Machine Learning and Deep Learning in Computational Toxicology. [ca. 2023]. In H. Hong (Hrsg.), Computational Methods in Engineering & the Sciences (1 st ed. 2023) [Cd]. Cham: Springer International Publishing. https://doi.org/10.1007/978-3-031-20730-3
ISO-690 (author-date, English)HONG, Huixiao (Hrsg.). 1 st ed. 2023. Cham: Springer International Publishing. ISBN 9783031207303.
Modern Language Association 9th editionHong, H., Herausgeber. „Machine Learning and Deep Learning in Computational Toxicology“. Computational Methods in Engineering & the Sciences, 1 st ed. 2023, cd, Springer International Publishing, 2023, https://doi.org/10.1007/978-3-031-20730-3.
Mohr Siebeck - Recht (Deutsch - Österreich): Machine Learning and Deep Learning in Computational Toxicology, 1 st ed. 2023. Aufl. Cham 2023.
Emerald - HarvardHong, H. (Hrsg.). (2023), Machine Learning and Deep Learning in Computational Toxicology, Computational Methods in Engineering & the Sciences, 1 st ed. 2023., Bd. , Springer International Publishing, Cham, verfügbar unter:https://doi.org/10.1007/978-3-031-20730-3.