Machine learning-based analysis of microfluidic device immobilized C. elegans for automated developmental toxicity testing

Machine learning-based analysis of microfluidic device immobilized C. elegans for automated developmental toxicity testing

Abstract Developmental toxicity (DevTox) tests evaluate the adverse effects of chemical exposures on an organism’s development. Although current testing primarily relies on large mammalian models, the emergence of new approach methodologies (NAMs) is encouraging industries and regulatory agencies to...

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Bibliographic Details
Main Authors: Andrew DuPlissis, Abhishri Medewar, Evan Hegarty, Adam Laing, Amber Shen, Sebastian Gomez, Sudip Mondal, Adela Ben-Yakar
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:Scientific Reports
Subjects:
U-Net
Few-shot learning
C. elegans
Developmental toxicity
Microfluidics
High-throughput screening
Online Access:https://doi.org/10.1038/s41598-024-84842-x
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