2022
DOI: 10.1016/j.neuro.2021.12.007
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Leveraging artificial intelligence to advance the understanding of chemical neurotoxicity

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Cited by 4 publications
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“…Thus, current research has a strong focus on elucidating the mechanistic underpinnings of pathologies associated with neurotoxicant exposure. Moreover, novel translational bioinformatics and chemo-informatics approaches, such as machine learning and artificial intelligence (AI) become increasingly important in predicting neurotoxicity (Aschner et al, 2022). This article collection covers both in vivo and in vitro studies performed in different species and features review articles elucidating the importance of closing data gaps regarding the pathomechanisms of neurotoxicants and other exogenous noxae harming the brain.…”
mentioning
confidence: 99%
“…Thus, current research has a strong focus on elucidating the mechanistic underpinnings of pathologies associated with neurotoxicant exposure. Moreover, novel translational bioinformatics and chemo-informatics approaches, such as machine learning and artificial intelligence (AI) become increasingly important in predicting neurotoxicity (Aschner et al, 2022). This article collection covers both in vivo and in vitro studies performed in different species and features review articles elucidating the importance of closing data gaps regarding the pathomechanisms of neurotoxicants and other exogenous noxae harming the brain.…”
mentioning
confidence: 99%