Proarrhythmic risk assessment of drugs by dV<sub>m</sub> /dt shapes using the convolutional neural network.

Jeong, Da Un; Yoo, Yedam; Marcellinus, Aroli; Kim, Ki-Suk; Lim, Ki Moo

Proarrhythmic risk assessment of drugs by dV_m /dt shapes using the convolutional neural network.

Jeong, Da Un; Yoo, Yedam; Marcellinus, Aroli; Kim, Ki-Suk; Lim, Ki Moo.

Afiliación

Jeong DU; Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi, Korea.
Yoo Y; Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi, Korea.
Marcellinus A; Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi, Korea.
Kim KS; R&D Center for Advanced Pharmaceuticals and Evaluation, Korea Institute of Toxicology, Daejeon, Korea.
Lim KM; Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi, Korea.

CPT Pharmacometrics Syst Pharmacol ; 11(5): 653-664, 2022 05.

Article en En | MEDLINE | ID: mdl-35579100

Asunto(s)

Torsades de Pointes; Simulación por Computador; Proteínas de Unión al ADN; Humanos; Redes Neurales de la Computación; Medición de Riesgo; Torsades de Pointes/inducido químicamente

Texto completo

Añadir a Mi BVS

Imprimir

XML

PubMed Links

Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Torsades de Pointes Tipo de estudio: Etiology_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: CPT Pharmacometrics Syst Pharmacol Año: 2022 Tipo del documento: Article Pais de publicación: Estados Unidos

Texto completo

Añadir a Mi BVS

Imprimir

XML

PubMed Links

Buscar en Google