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This could, in turn, lead to various neurological disorders such as Parkinson's or Huntington's disease as well as various dementias. Toxicity assessment is often done by pathologists after these exposures by qualitatively or semiquantitatively grading the severity of neurotoxicity in histopathology slides. Quantification of the extent of neurotoxicity supports qualitative histopathological analysis and provides a better understanding of the global extent of brain damage. Stereological techniques such as the utilization of an optical fractionator provide an unbiased quantification of the neuronal damage; however, the process is time\u2010consuming. Advent of whole slide imaging (WSI) introduced digital image analysis which made quantification of neurotoxicity automated, faster and with reduced bias, making statistical comparisons possible. Although automated to a certain level, simple digital image analysis requires manual efforts of experts which is time\u2010consuming and limits analysis of large datasets. Digital image analysis coupled with a deep learning artificial intelligence model provides a good alternative solution to time\u2010consuming stereological and simple digital analysis. Deep learning models could be trained to identify damaged or dead neurons in an automated fashion. This review has focused on and discusses studies demonstrating the role of deep learning in segmentation of brain regions, toxicity detection and quantification of degenerated neurons as well as the estimation of area\/volume of degeneration.<\/jats:p>","DOI":"10.1002\/jat.4098","type":"journal-article","created":{"date-parts":[[2020,11,3]],"date-time":"2020-11-03T03:20:31Z","timestamp":1604373631000},"page":"996-1006","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Quantitative neurotoxicology: Potential role of artificial intelligence\/deep learning approach"],"prefix":"10.1002","volume":"41","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7392-287X","authenticated-orcid":false,"given":"Anshul","family":"Srivastava","sequence":"first","affiliation":[{"name":"Center for Drug Evaluation and Research US Food and Drug Administration  Silver Spring Maryland 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