hERG-toxicity prediction using traditional machine learning and advanced deep learning techniques

The rise of artificial intelligence (AI) based algorithms has gained a lot of interest in the pharmaceutical development field. Our study demonstrates utilization of traditional machine learning techniques such as random forest (RF), support-vector machine (SVM), extreme gradient boosting (XGBoost),...

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Detalles Bibliográficos
Autores principales: Ylipää, Erik, Chavan, Swapnil, Bånkestad, Maria, Broberg, Johan, Glinghammar, Björn, Norinder, Ulf, Cotgreave, Ian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10493507/
https://www.ncbi.nlm.nih.gov/pubmed/37701072
http://dx.doi.org/10.1016/j.crtox.2023.100121

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10493507/
https://www.ncbi.nlm.nih.gov/pubmed/37701072
http://dx.doi.org/10.1016/j.crtox.2023.100121

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