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Machine-learning based prediction models for assessing skin irritation and corrosion potential of liquid chemicals using physicochemical properties by XGBoost

Crossref DOI link: https://doi.org/10.1007/s43188-022-00168-8

Published Online: 2023-01-23

Published Print: 2023-04

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Kang, Yeonsoo

Kim, Myeong Gyu

Lim, Kyung-Min https://orcid.org/0000-0002-1517-7680
Funding

Funding for this research was provided by:

Ministry of Environment (2021002970001)

Ministry of Environment (1485017976)

Ministry of Health and Welfare (the Korea Cosmetic Industry Institute (KCII))
License Information

Text and Data Mining valid from 2023-01-23

Version of Record valid from 2023-01-23
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Article History

Received: 31 October 2022

Revised: 15 December 2022

Accepted: 23 December 2022

First Online: 23 January 2023

Declarations

:

: The authors have no conflict of interest to declare.

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