Cold-Start Problems in Data-Driven Prediction of Drug–Drug Interaction Effects

Cold-Start Problems in Data-Driven Prediction of Drug–Drug Interaction Effects

Combining drugs, a phenomenon often referred to as polypharmacy, can induce additional adverse effects. The identification of adverse combinations is a key task in pharmacovigilance. In this context, in silico approaches based on machine learning are promising as they can learn from a limited number...

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Bibliographic Details
Main Authors: Pieter Dewulf, Michiel Stock, Bernard De Baets
Format: Article
Language:English
Published: MDPI AG 2021-05-01
Series:Pharmaceuticals
Subjects:
polypharmacy
drug–drug interaction
prediction
cross-validation
machine learning
cold-start problems
Online Access:https://www.mdpi.com/1424-8247/14/5/429

Internet

https://www.mdpi.com/1424-8247/14/5/429

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