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Updated: May 10, 2026

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CLSSATP:对比式学习和自我监督的学习模型用于水生物毒性预测.

Ye Lin1, Xin Yang2, Mingxuan Zhang3

  • 1College of Computer Science and Technology, Jilin University, Changchun, 130012, China.

Aquatic toxicology (Amsterdam, Netherlands)
|January 13, 2025
PubMed
概括

一个新的深度学习模型,CLSSATP (对比自主监督学习),准确地预测水生环境中的有机毒性. 这种方法通过了解化学物质对水生生物的影响来加强环境保护.

关键词:
对水生有毒性的水生毒性相反的学习学习.深度学习是一种深度学习.多任务模式的模型.自主监督学习学习

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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...