2023
DOI: 10.1016/j.medidd.2022.100149
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Improved prediction of drug-drug interactions using ensemble deep neural networks

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Cited by 28 publications
(7 citation statements)
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“…In addition, the use of deep learning facilitates the prediction of drug side effects that may not have been identified during clinical trials and the development of different architectures to predict potential side effects for drugs in the clinical development stage. Different ensemble deep learning networks can be improved for the predictive performance of ADRs that help in supporting medical decisions and drug development [26][27][28].…”
Section: Proposed Model Architecturementioning
confidence: 99%
“…In addition, the use of deep learning facilitates the prediction of drug side effects that may not have been identified during clinical trials and the development of different architectures to predict potential side effects for drugs in the clinical development stage. Different ensemble deep learning networks can be improved for the predictive performance of ADRs that help in supporting medical decisions and drug development [26][27][28].…”
Section: Proposed Model Architecturementioning
confidence: 99%
“…The research 43 examined, a novel ensemble neural network model, proposed to improve the accuracy of predicting drug-drug interactions. In this study, the authors introduce a super-smart computer model that can predict interactions between 86 different drugs with almost 94% accuracy.…”
Section: Related Workmentioning
confidence: 99%
“…The representation of drug compounds through the simplified molecular-input line-entry system (SMILES) notation is a common practice in AI-based drug discovery. SMILES notations of drugs can be transformed into molecular fingerprints such as Morgan fingerprints, enabling the construction of machine learning (ML) models for virtual screening to predict a spectrum of drug properties, including toxicity, 1 , 2 , 3 drug-drug interaction, 4 , 5 , 6 , 7 and drug-target interactions. 8 , 9 , 10 , 11 Such molecular fingerprints have also been instrumental in precision medicine, guiding personalized drug screening (PSD) using gene expressions and multi-omics data.…”
Section: Introductionmentioning
confidence: 99%