Aug 2026· Interdisciplinary Sciences Computational Life Sciences· 0 citations· 29 references
Medicine
TL;DR
DynMedRec captures fine-grained drug information by modeling the interactions between substructures and employing a clinical-context query mechanism to generate adaptive molecular representations, and integrates structural correlations among medical codes to enhance visit-level patient representations.
Experimental results demonstrate that MoTRANet outperforms existing mainstream baseline methods in terms of Jaccard, F1, and PRAUC, while achieving a relatively low DDI rate, validating the model's accuracy and safety.
Peng-Tao Jia, Jun-Hao Gao, Jing-Tao Sha et al.· IEEE transactions on computa...· 0 citations
MGRec is a framework that shifts learning from discrete prescription prediction to condition-aware modeling in a continuous molecular representation space and introduces a DDI (drug-drug interaction)-guided latent regularization to integrate drug interaction knowledge at the representation level to improve clinical saf...
Jin-Ke Feng, Wenjie Du· Proceedings of the Thirty-Fi...· 0 citations
XMERec is proposed, a dual-level medication recommendation framework that jointly models medical entity interactions and short-term visit sequences and is fused with an association-guided correction mechanism to improve recommendation accuracy and safety.
Qing-Chuan Xu, K. Che, Jia-Feng Li et al.· IEEE Access· 0 citations
SpecTD-MR, a novel medication recommendation framework for Disease Spectrum-aware and Time-evolving Dependency Learning, is proposed that surpasses state-of-the-art baselines in accuracy, while providing visualizable structural associations to support insights into dynamic disease evolution.
Yi-Shuo Li, Cong Wang, Shou-Jin Wang et al.· ACM Transactions on Informat...· 1 citation
The NexusOpti model, incorporating the Enhanced Gated Recurrent Unit (E-GRU) layer, outperforms the existing GRU model in terms of NDCG and Hit Ratio metrics and highlights the effectiveness of the model in advancing personalised, safer, and data-driven medication prescriptions.
Harichandra Khalingarajah, A. Vasudevan, P. Abinaya et al.· Scientific Reports· 0 citations
A novel framework named Multi-Knowledge Medication recommendation is proposed, which introduces a cross-modal medication encoder capable of aligning heterogeneous modalities into a unified representation space and explicitly mitigates the bucket effect, enabling robust recommendation performance even in sparse knowledg...
Hai-Xu Ma, Guan-Yong Wu, Shi-Zhuo Mu et al.· Applied intelligence (Boston...· 0 citations
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