Model and Strategy for Predicting and Discovering Drug-Drug Interactions - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Journal Articles Studies in Health Technology and Informatics Year : 2023

Model and Strategy for Predicting and Discovering Drug-Drug Interactions

Abstract

Taking several medications at the same time is an increasingly common phenomenon in our society. The combination of drugs is certainly not without risk of potentially dangerous interactions. Taking into account all possible interactions is a very complex task as it is not yet known what all possible interactions between drugs and their types are. Machine learning based models have been developed to help with this task. However, the output of these models is not structured enough to be integrated in a clinical reasoning process on interactions. In this work, we propose a clinically relevant and technically feasible model and strategy for drug interactions.
Fichier principal
Vignette du fichier
SHTI-302-SHTI230248.pdf (267.65 Ko) Télécharger le fichier
Origin Publication funded by an institution

Dates and versions

hal-04162795 , version 1 (05-12-2023)

Licence

Identifiers

Cite

Abdelmalek Mouazer, Nada Boudegzdame, Karima Sedki, Rosy Tsopra, Jean-Baptiste Lamy. Model and Strategy for Predicting and Discovering Drug-Drug Interactions. Studies in Health Technology and Informatics, 2023, Studies in Health Technology and Informatics, ⟨10.3233/SHTI230248⟩. ⟨hal-04162795⟩
46 View
32 Download

Altmetric

Share

Gmail Mastodon Facebook X LinkedIn More