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Uncertainty-aware machine learning to predict non-cancer human toxicity for the global chemicals market

2025-03-07

Abstract excerpt

<title>Abstract</title> <p>Humans are exposed to many chemicals, yet limited toxicity data hinder effectively managing their impact on human health. High-performing machine learning models hold potential for addressing this gap, but their uncharacterized prediction performance across the wider chemical space undermines confidence in their results. We developed uncertainty-aware models to predict reproductive/deve...

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Literature Corpus work
b15bbc15-80a5-5b8f-834f-8c5ff32fbf22
DOI
10.21203/rs.3.rs-6103978/v1
Open publication

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Uncertainty-aware machine learning to predict non-cancer human toxicity for the global chemicals marketDOI 10.21203/rs.3.rs-6103978/v1
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