Machine Learning Methods for Endocrine Disrupting Potential Identification Based on Single-Cell Data
Humans are continuously exposed to a variety of toxicants and chemicals which is exacerbated during and after environmental catastrophes such as floods, earthquakes, and hurricanes. The hazardous chemical mixtures generated during these events threaten the health and safety of humans and other livin...
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Bibliographische Detailangaben
| Veröffentlicht in: | Chemical engineering science. - 1998. - 281(2023) vom: 05. Nov.
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| 1. Verfasser: |
Aghayev, Zahir
(VerfasserIn) |
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| Weitere Verfasser: |
Szafran, Adam T,
Tran, Anh,
Ganesh, Hari S,
Stossi, Fabio,
Zhou, Lan,
Mancini, Michael A,
Pistikopoulos, Efstratios N,
Beykal, Burcu |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2023
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| Zugriff auf das übergeordnete Werk: | Chemical engineering science
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| Schlagworte: | Journal Article
Classification analysis
Endocrine disrupting chemicals
Estrogen receptor activity
High throughput microscopy
Machine learning
Predictive modeling |
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