cirpublications.com-rgVT-1790880681-b212276511 1790880681 Clinical Intelligence Research Press info@cirpublications.com Clinical Intelligence Research Press Journal of Artificial Intelligence for Healthcare Systems J. Artif. Intell. Healthc. Syst. 3149-8981 2022 1 2 Daniel Fischer Laura Meier Thomas Braun Stefan Koch Felix Roth 2022 10.68159/b212276511 https://cirpublications.com/pub/journal/1/article/b212276511 Ouchi K, Lindvall C, Chai PR, Boyer EW. Machine learning to predict, detect, and intervene older adults vulnerable for adverse drug events in the emergency department. J Med Toxicol. 2018;14(3):248-52. 10.1007/s13181-018-0674-4 Al-Rabeah MH, Lakizadeh A. Prediction of drug-drug interaction events using graph neural networks based feature extraction. Sci Rep. 2022;12(1):15590. 10.1038/s41598-022-19895-8 Wang M, Wang H, Liu X, Ma X, Wang B. Drug-drug interaction predictions via knowledge graph and text embedding: instrument validation study. JMIR Med Inform. 2021;9(6):e28277. 10.2196/28277 Karim MR, Cochez M, Jares JB, Uddin M, Beyan O, Decker S. Drug-drug interaction prediction based on knowledge graph embeddings and convolutional-LSTM network. In: Proc 10th ACM Int Conf Bioinform Comput Biol Health Inform. 2019. p. 113-23. 10.1145/3307339.3342161 Lin X, Quan Z, Wang ZJ, Ma T, Zeng X. KGNN: knowledge graph neural network for drug-drug interaction prediction. In: Proc IJCAI. 2020. p. 2739-45. Hong Y, Luo P, Jin S, Liu X. LaGAT: link-aware graph attention network for drug-drug interaction prediction. Bioinformatics. 2022;38(24):5406-12. Deng Y, Xu X, Qiu Y, Xia J, Zhang W, Liu S. A multimodal deep learning framework for predicting drug-drug interaction events. Bioinformatics. 2020;36(15):4316-22. Yu Y, Huang K, Zhang C, Glass LM, Sun J, Xiao C. SumGNN: multi-typed drug interaction prediction via efficient knowledge graph summarization. Bioinformatics. 2021;37(18):2988-95. Zhang W, Kuang Z, Peissig P, Page D. Adverse drug reaction discovery from electronic health records with deep neural networks. In: Proc ACM Conf Health Inference Learn. 2020. p. 30-39. 10.1145/3368555.3384453 Han X, Xie R, Li X, Li J. SmileGNN: drug-drug interaction prediction based on the SMILES and graph neural network. Life (Basel). 2022;12(2):319. 10.3390/life12020319 Feng YH, Zhang SW. Prediction of drug-drug interaction using an attention-based graph neural network on drug molecular graphs. Molecules. 2022;27(9):3004. 10.3390/molecules27093004 Olekhnovitch R, Hoertel N, Limosin F, Blanco C, Olfson M, Fagot-Campagna A, et al. Using filled prescription sequences to rank antidepressants according to their acceptability in the general population: the Constances cohort. J Psychiatr Res. 2020;123:72-80. 10.1016/j.jpsychires.2020.01.019 Asada M, Miwa M, Sasaki Y. Extracting drug-drug interactions with attention CNNs. In: Proc BioNLP 2017. 2017. p. 9-18. Liu S, Zhang Y, Cui Y, Qiu Y, Deng Y, Zhang Z, et al. Enhancing drug-drug interaction prediction using deep attention neural networks. IEEE/ACM Trans Comput Biol Bioinform. 2023;20(2):976-85. 10.1109/TCBB.2022.3172215 Yang Z, Zhong W, Lv Q, Chen CY. Learning size-adaptive molecular substructures for explainable drug-drug interaction prediction by substructure-aware graph neural network. Chem Sci. 2022;13(29):8693-703. 10.1039/D2SC02218D Rodrigues AD, editor. Drug-Drug Interactions. Boca Raton (FL): CRC Press; 2019. Niu J, Straubinger RM, Mager DE. Pharmacodynamic drug-drug interactions. Clin Pharmacol Ther. 2019;105(6):1395-406. 10.1002/cpt.1434 Li Z, Liu F, Yang W, Peng S, Zhou J. A survey of convolutional neural networks: analysis, applications, and prospects. IEEE Trans Neural Netw Learn Syst. 2022;33(12):6999-7019. 10.1109/TNNLS.2021.3084827 Patton K, Borshoff DC. Adverse drug reactions. Anaesthesia. 2018;73(Suppl 1):76-84. 10.1111/anae.14137 Vazquez SR. Drug-drug interactions in an era of multiple anticoagulants: a focus on clinically relevant drug interactions. Blood. 2018;132(21):2230-9. 10.1182/blood-2018-06-848747 He C, Liu Y, Li H, Zhang H, Mao Y, Qin X, et al. Multi-type feature fusion based on graph neural network for drug-drug interaction prediction. BMC Bioinformatics. 2022;23(1):224. 10.1186/s12859-022-04761-z Carpenter M, Berry H, Pelletier AL. Clinically relevant drug-drug interactions in primary care. Am Fam Physician. 2019;99(9):558-64. Zhang T, Leng J, Liu Y. Deep learning for drug-drug interaction extraction from the literature: a review. Brief Bioinform. 2021;21(5):1609-27. Lyu T, Gao J, Tian L, Li Z, Zhang P, Zhang J. MDNN: a multimodal deep neural network for predicting drug-drug interaction events. In: Proc IJCAI. 2021. p. 3536-42. Jin W, Barzilay R, Jaakkola T. Hierarchical generation of molecular graphs using structural motifs. In: Proc Int Conf Mach Learn. 2020;119:4839-48. Sudsakorn S, Bahadduri P, Fretland J, Lu C. 2020 FDA drug-drug interaction guidance: a comparison analysis and action plan by pharmaceutical industrial scientists. Curr Drug Metab. 2020;21(6):403-26. 10.2174/1389200221666200622094105