Timezone: »
AI-empowered drug recommendation has become an important task in healthcare research areas, which offers an additional perspective to assist human doctors with more accurate and more efficient drug prescriptions. Generally, drug recommendation is based on patients' diagnosis results in the electronic health records. We assume that there are three key factors to be addressed in drug recommendation: 1) elimination of recommendation bias due to limitations of observable information, 2) better utilization of historical health condition and 3) coordination of multiple drugs to control safety. To this end, we propose DrugRec, a causal inference based drug recommendation model. The causal graphical model can identify and deconfound the recommendation bias with front-door adjustment. Meanwhile, we model the multi-visit in the causal graph to characterize a patient's historical health conditions. Finally, we model the drug-drug interactions (DDIs) as the propositional satisfiability (SAT) problem, and solving the SAT problem can help better coordinate the recommendation. Comprehensive experiment results show that our proposed model achieves state-of-the-art performance on the widely used datasets MIMIC-III and MIMIC-IV, demonstrating the effectiveness and safety of our method.
Author Information
Hongda Sun (Gaoling School of Artificial Intelligence, Renmin University of China)
Shufang Xie (Renmin University of China)
Shuqi Li (Renmin University of China)
Yuhan Chen (Renmin University of China)
Ji-Rong Wen (Renmin University of China)
Rui Yan (Peking University)
More from the Same Authors
-
2022 Poster: Log-Polar Space Convolution Layers »
Bing Su · Ji-Rong Wen -
2023 Poster: Lift Yourself Up: Retrieval-augmented Text Generation with Self-Memory »
Xin Cheng · Di Luo · Xiuying Chen · Lemao Liu · Dongyan Zhao · Rui Yan -
2023 Poster: FABind: Fast and Accurate Protein-Ligand Binding »
Qizhi Pei · Kaiyuan Gao · Lijun Wu · Jinhua Zhu · Yingce Xia · Shufang Xie · Tao Qin · Kun He · Tie-Yan Liu · Rui Yan -
2023 Poster: Reward Imputation with Sketching for Contextual Batched Bandits »
Xiao Zhang · Ninglu Shao · Zihua Si · Jun Xu · Wenhan Wang · Hanjing Su · Ji-Rong Wen -
2023 Poster: SpokenWOZ: A Large-Scale Speech-Text Dataset for Spoken Task-Oriented Dialogue in Multiple Domains »
Shuzheng Si · Wentao Ma · Haoyu Gao · Yuchuan Wu · Ting-En Lin · Yinpei Dai · Hangyu Li · Rui Yan · Fei Huang · Yongbin Li -
2023 Poster: REASONER: An Explainable Recommendation Dataset with Comprehensive Labeling Ground Truths »
Xu Chen · Jingsen Zhang · Lei Wang · Quanyu Dai · Zhenhua Dong · Ruiming Tang · Rui Zhang · Li Chen · Xin Zhao · Ji-Rong Wen -
2023 Poster: Evaluating and Improving Tool-Augmented Computation-Intensive Math Reasoning »
Beichen Zhang · Kun Zhou · Xilin Wei · Xin Zhao · Jing Sha · Shijin Wang · Ji-Rong Wen -
2022 Spotlight: Lightning Talks 2B-2 »
Chenjian Gao · Rui Ding · Lingzhi LI · Fan Yang · Xingting Yao · Jianxin Li · Bing Su · Zhen Shen · Tongda Xu · Shuai Zhang · Ji-Rong Wen · Lin Guo · Fanrong Li · Kehua Guo · Zhongshu Wang · Zhi Chen · Xiangyuan Zhu · Zitao Mo · Dailan He · Hui Xiong · Yan Wang · Zheng Wu · Wenbing Tao · Jian Cheng · Haoyi Zhou · Li Shen · Ping Tan · Liwei Wang · Hongwei Qin -
2022 Spotlight: Log-Polar Space Convolution Layers »
Bing Su · Ji-Rong Wen -
2022 Poster: Convolutional Neural Networks on Graphs with Chebyshev Approximation, Revisited »
Mingguo He · Zhewei Wei · Ji-Rong Wen -
2021 Poster: Stylized Dialogue Generation with Multi-Pass Dual Learning »
Jinpeng Li · Yingce Xia · Rui Yan · Hongda Sun · Dongyan Zhao · Tie-Yan Liu -
2021 Poster: Compressed Video Contrastive Learning »
Yuqi Huo · Mingyu Ding · Haoyu Lu · Nanyi Fei · Zhiwu Lu · Ji-Rong Wen · Ping Luo -
2020 Poster: Scalable Graph Neural Networks via Bidirectional Propagation »
Ming Chen · Zhewei Wei · Bolin Ding · Yaliang Li · Ye Yuan · Xiaoyong Du · Ji-Rong Wen -
2018 Poster: Domain-Invariant Projection Learning for Zero-Shot Recognition »
An Zhao · Mingyu Ding · Jiechao Guan · Zhiwu Lu · Tao Xiang · Ji-Rong Wen