Prediction of frequencies of drug side effects using social recommendation algorithm based on multi-feature fusion

Qingsheng Chen; Xiangmin Ji

doi:10.1117/12.3003844

11 October 2023 Prediction of frequencies of drug side effects using social recommendation algorithm based on multi-feature fusion

Qingsheng Chen, Xiangmin Ji

Author Affiliations +

Proceedings Volume 12800, Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023); 128002Y (2023) https://doi.org/10.1117/12.3003844
Event: 6th International Conference on Computer Information Science and Application Technology (CISAT 2023), 2023, Hangzhou, China

Abstract

Aiming at the cold start problem and the limited prediction performance associated with sparse data in drug side effects frequencies study, we propose a matrix factorization method called Social Recommendation algorithm based on Multi Feature Fusion (SRMFF). First, the trust propagation mechanism is introduced into the matrix factorization, and the data sparsity and cold start drugs are alleviated by factorizing the drug side effect score matrix and drug trust matrix concurrently. Second, we select SIDER dataset and the drug Azvudine against COVID-19 as the experiment data. The results show that SRMFF can predict the frequencies of drug side effects effectively and have excellent performance in multiple performance indicators. At the same time, SRMFF can also predict the frequencies of side effects of new drug in the population.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Qingsheng Chen and Xiangmin Ji "Prediction of frequencies of drug side effects using social recommendation algorithm based on multi-feature fusion", Proc. SPIE 12800, Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023), 128002Y (11 October 2023); https://doi.org/10.1117/12.3003844

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KEYWORDS

Matrices

Performance modeling

Tablets

Evolutionary algorithms

Feature fusion

Vacuum ultraviolet

Databases

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