Cargando…
MSDRP: a deep learning model based on multisource data for predicting drug response
MOTIVATION: Cancer heterogeneity drastically affects cancer therapeutic outcomes. Predicting drug response in vitro is expected to help formulate personalized therapy regimens. In recent years, several computational models based on machine learning and deep learning have been proposed to predict dru...
Autores principales: | Zhao, Haochen, Zhang, Xiaoyu, Zhao, Qichang, Li, Yaohang, Wang, Jianxin |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10474952/ https://www.ncbi.nlm.nih.gov/pubmed/37606993 http://dx.doi.org/10.1093/bioinformatics/btad514 |
Ejemplares similares
-
Identifying the serious clinical outcomes of adverse reactions to drugs by a multi-task deep learning framework
por: Zhao, Haochen, et al.
Publicado: (2023) -
Deep-Learning Model for Influenza Prediction From Multisource Heterogeneous Data in a Megacity: Model Development and Evaluation
por: Yang, Liuyang, et al.
Publicado: (2023) -
Multisource Deep Transfer Learning Based on Balanced Distribution Adaptation
por: Gao, Peng, et al.
Publicado: (2022) -
Visual Evaluation of Urban Streetscape Design Supported by Multisource Data and Deep Learning
por: Feng, Guanqing, et al.
Publicado: (2022) -
Health Outcomes from Home Hospitalization: Multisource Predictive Modeling
por: Calvo, Mireia, et al.
Publicado: (2020)