An Explainable Supervised Machine Learning Model for Predicting Respiratory Toxicity of Chemicals Using Optimal Molecular Descriptors

An Explainable Supervised Machine Learning Model for Predicting Respiratory Toxicity of Chemicals Using Optimal Molecular Descriptors

Respiratory toxicity is a serious public health concern caused by the adverse effects of drugs or chemicals, so the pharmaceutical and chemical industries demand reliable and precise computational tools to assess the respiratory toxicity of compounds. The purpose of this study is to develop quantita...

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Bibliographic Details
Main Authors:	Keerthana Jaganathan, Hilal Tayara, Kil To Chong
Format:	Article
Language:	English
Published:	MDPI AG 2022-04-01
Series:	Pharmaceutics
Subjects:	respiratory toxicity molecular descriptors feature selection machine learning SHapley Additive exPlanations
Online Access:	https://www.mdpi.com/1999-4923/14/4/832

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