Predicting Dose-Dependent Carcinogenicity of Chemical Mixtures Using a Novel Hybrid Neural Network Framework and Mathematical Approach
This study addresses the challenge of assessing the carcinogenic potential of hazardous chemical mixtures, such as per- and polyfluorinated substances (PFASs), which are known to contribute significantly to cancer development. Here, we propose a novel framework called HNN<sub>MixCancer</sub...
Main Authors: | , |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-07-01
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Series: | Toxics |
Subjects: | |
Online Access: | https://www.mdpi.com/2305-6304/11/7/605 |