Kerstin von Borries - JoVE Visualize

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Nature Communications|January 7, 2026

Uncertainty-aware machine learning to predict non-cancer human toxicity for the global chemicals marketKerstin von Borries, Katie V Beckwith, Jonathan M Goodman, et al.

Environmental Science & Technology|November 1, 2023

Potential for Machine Learning to Address Data Gaps in Human Toxicity and Ecotoxicity CharacterizationKerstin von Borries, Hanna Holmquist, Marissa Kosnik, et al.

Environmental Science & Technology|May 2, 2024

Two-Stage Machine Learning-Based Approach to Predict Points of Departure for Human Noncancer and Developmental/Reproductive EffectsJacob Kvasnicka, Nicolò Aurisano, Kerstin von Borries, et al.

Environmental Research|July 28, 2026

Applying in silico ecotoxicity prediction to extensive datasets to support safer and more sustainable discovery chemistryFotini Nikiforou, Gianluca Selvestrel, Elisabeth Söderberg, et al.

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Showing results (1-10 of 4) with videos related to

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Pageof 1

Nature Communications|January 7, 2026

Uncertainty-aware machine learning to predict non-cancer human toxicity for the global chemicals marketKerstin von Borries, Katie V Beckwith, Jonathan M Goodman, et al.

Environmental Science & Technology|November 1, 2023

Potential for Machine Learning to Address Data Gaps in Human Toxicity and Ecotoxicity CharacterizationKerstin von Borries, Hanna Holmquist, Marissa Kosnik, et al.

Environmental Science & Technology|May 2, 2024

Two-Stage Machine Learning-Based Approach to Predict Points of Departure for Human Noncancer and Developmental/Reproductive EffectsJacob Kvasnicka, Nicolò Aurisano, Kerstin von Borries, et al.

Environmental Research|July 28, 2026

Applying in silico ecotoxicity prediction to extensive datasets to support safer and more sustainable discovery chemistryFotini Nikiforou, Gianluca Selvestrel, Elisabeth Söderberg, et al.

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