Accurate clinical toxicity prediction using multi-task deep neural nets and contrastive molecular explanations

Explainable machine learning for molecular toxicity prediction is a promising approach for efficient drug development and chemical safety. A predictive ML model of toxicity can reduce experimental cost and time while mitigating ethical concerns by significantly reducing animal and clinical testing....

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Detalles Bibliográficos
Autores principales: Sharma, Bhanushee, Chenthamarakshan, Vijil, Dhurandhar, Amit, Pereira, Shiranee, Hendler, James A., Dordick, Jonathan S., Das, Payel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10039880/
https://www.ncbi.nlm.nih.gov/pubmed/36966203
http://dx.doi.org/10.1038/s41598-023-31169-8

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10039880/
https://www.ncbi.nlm.nih.gov/pubmed/36966203
http://dx.doi.org/10.1038/s41598-023-31169-8

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