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Updated: Jul 10, 2026

A High-throughput Assay for the Prediction of Chemical Toxicity by Automated Phenotypic Profiling of Caenorhabditis elegans
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使用超级学习者来预测大鼠的化学急性毒性

Yuzhe Li1, Bixuan Wang1, Fujun Ma2

  • 1School of Materials Science and Engineering, Beihang University, Beijing 100191, China.

Journal of hazardous materials
|October 30, 2024
PubMed
概括

这项研究引入了一种超级学习者模型,用于预测化学物质中位数致命剂量 (LD50),为化学安全评估提供了对动物试验的经济有效和伦理替代方案.

关键词:
化学品 化学品 化学品 化学品LD(50) 的时间.机器学习是机器学习.它们是老鼠,老鼠,老鼠.超级瘦身的超级瘦身者

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相关概念视频

Toxicity Testing in Animals01:23

Toxicity Testing in Animals

Toxicity tests in animals are grounded on two main assumptions: first, the effects observed in laboratory animals can be extrapolated to humans, especially when adjusted for body surface area; second, high-dose exposure in animals is essential to identify potential human hazards from lower doses. This is based on the quantal dose-response concept, which faces the challenge of extrapolating results from relatively few test animals to much larger human populations. For example, a 0.01% incidence...