Combinatorial drug treatment is common in the clinic for treating patients with complex diseases. However, it also increases the chance of drug-drug interactions (DDI). As a major type of adverse drug events, DDIs may lead to patient hospitalization or even drug withdrawal from market [[1], ...
Drug–drug interactionsGraph auto-encoderHeterogeneous networkResidual graph convolutional networkDrug–drug interaction refers to taking the two drugs may produce certain reaction which may be a threat to patients' health, or enhance the efficacy helpful for medical work. Therefore, it is necessary to...
BMC Bioinformatics 2022, 23(Suppl 4):129 https://doi.org/10.1186/s12859-022-04664-4 BMC Bioinformatics RESEARCH Open Access DualGCN: a dual graph convolutional network model to predict cancer drug response Tianxing Ma1, Qiao Liu2, Haochen Li3, Mu Zhou4, Rui Jiang1 and ...
Whole genome sequencing of multiple Leishmania donovani clinical isolates provides insights into population structure and mechanisms of drug resistance Visceral leishmaniasis is a potentially fatal disease endemic to large parts of Asia and Africa, primarily caused by the protozoan parasite Leishmania dono....
翻译:夏佳豪原文地址:https://news.stanford.edu/2018/07/10/ai-predicts-drug-pair-side-effects/?from=singlemessage论文地址:https://academic.oup.com/bioinformatics/article/34/13/i457/5045770 推荐阅读 图网络——悄然兴起的深度学习新浪潮 ◆◆◆ ...
Ma, T., Liu, Q., Li, H.et al.DualGCN: a dual graph convolutional network model to predict cancer drug response.BMC Bioinformatics23,129 (2022). https://doi.org/10.1186/s12859-022-04664-4Contents Aim…
DDI-GCN: Drug-drug interaction prediction via explainable graph convolutional networks 2023, Artificial Intelligence in Medicine Citation Excerpt : First, the model architecture can be explored and improved. As regular GCNs may suffer from complexity and redundant node information in the process of propa...
Polypharmacy involves an individual using many medications at the same time and is a frequent healthcare technique used to treat complex medical disorders. Nevertheless, it also presents substantial risks of negative medication responses and interactions
为改进当前人体摔倒检测方法场景适应能力弱,易误检等不足,提出了一种基于人体骨骼关键点和GCN结合的人体摔倒检测模型.在CrownHuman,COCO2017,Le2i等数据集上进行对比试验,试验结果表明优化后的YOLOX人体目标检测算法的平均准确率达到了50.66%,较YOLOv3,YOLOv5提高了9.83%和3.97%.人体姿态估计算法的平均准确率达到了71...
Regulation of cell size 0.00614 Response to drug 0.00483 Cell growth 0.011 Selected categories of a Gene Set Enrichment Analysis using Fatiscan (Medina et al. [51]) on the expression values of 16-days-old Arabidopsis wild-type Landsberg erecta seedlings treated with glyphosate, as described in ...