SSPNet: Leveraging Robust Medication Recommendation with History and Knowledge

Zhang, Haodi; Wen, Jiawei; Li, Jiahong; Song, Yuanfeng; Zhang, Liang-Jie; Ma, Lin

doi:10.24963/ijcai.2025/1052

SSPNet: Leveraging Robust Medication Recommendation with History and Knowledge

Haodi Zhang, Jiawei Wen, Jiahong Li, Yuanfeng Song, Liang-Jie Zhang, Lin Ma

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Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence. AI4Tech: AI Enabling Technologies. Pages 9465-9473.

https://doi.org/10.24963/ijcai.2025/1052

Keywords

Domain-specific AI4Tech: AI4Care and AI4Health
Domain-specific AI4Tech: AI4Medicine and AI4Drug

Abstract

Automated medication recommendation is a crucial task within the domain of artificial intelligence in healthcare, where recommender systems are supposed to deliver precise, personalized drug combinations tailored to the evolving health states of patients. Existing approaches often treat clinical records (e.g., diagnoses, procedures) as isolated or unified entities, neglecting the inherent set-structured nature of medical data and the need to model interdependencies among clinical elements. To address the gap, we propose SSPNet, a novel end-to-end framework designed to process complete clinical record sets and directly generate optimal medication sets. SSPNet employs a set-based encoder to effectively capture and represent a patient's health condition from the electronic health records (EHRs), while a permutation-consistent decoder predicts the entire medication combination as a set. In addition, we introduce a novel personalized representation mechanism to capture the drugs previously used by individual patients. Extensive experiments on MIMIC-Ⅲ and MIMIC-Ⅳ data sets reveal that SSPNet surpasses existing state-of-the-art methods in the accuracy of medication recommendations.

Haodi Zhang, Jiawei Wen, Jiahong Li, Yuanfeng Song, Liang-Jie Zhang, and Lin Ma. 2025. SSPNet: Leveraging Robust Medication Recommendation with History and Knowledge. In Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-25. IJCAI, 9465–9473. https://doi.org/10.24963/ijcai.2025/1052

@inproceedings{ijcai2025p1052,
  title     = {SSPNet: Leveraging Robust Medication Recommendation with History and Knowledge},
  author    = {Zhang, Haodi and Wen, Jiawei and Li, Jiahong and Song, Yuanfeng and Zhang, Liang-Jie and Ma, Lin},
  booktitle = {Proceedings of the Thirty-Fourth International Joint Conference on
               Artificial Intelligence, {IJCAI-25}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {James Kwok},
  pages     = {9465--9473},
  year      = {2025},
  month     = {8},
  note      = {AI4Tech: AI Enabling Technologies},
  doi       = {10.24963/ijcai.2025/1052},
  url       = {https://doi.org/10.24963/ijcai.2025/1052},
}

TY  - CPAPER
TI  - SSPNet: Leveraging Robust Medication Recommendation with History and Knowledge
AU  - Zhang, Haodi
AU  - Wen, Jiawei
AU  - Li, Jiahong
AU  - Song, Yuanfeng
AU  - Zhang, Liang-Jie
AU  - Ma, Lin
T2  - Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-25
PB  - International Joint Conferences on Artificial Intelligence Organization
PY  - 2025
SP  - 9465
EP  - 9473
DO  - 10.24963/ijcai.2025/1052
UR  - https://doi.org/10.24963/ijcai.2025/1052
ER  -