Learning from low-rank multimodal representations for predicting disease-drug associations

Learning from low-rank multimodal representations for predicting disease-drug associations

Abstract Background Disease-drug associations provide essential information for drug discovery and disease treatment. Many disease-drug associations remain unobserved or unknown, and trials to confirm these associations are time-consuming and expensive. To better understand and explore these valuabl...

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Bibliographic Details
Main Authors: Pengwei Hu, Yu-an Huang, Jing Mei, Henry Leung, Zhan-heng Chen, Ze-min Kuang, Zhu-hong You, Lun Hu
Format: Article
Language:English
Published: BMC 2021-11-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Disease-drug associations prediction
Low-rank tensors
Multimodal fusion
Online Access:https://doi.org/10.1186/s12911-021-01648-x

Internet

https://doi.org/10.1186/s12911-021-01648-x

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