- Promoting appropriate medication use by leveraging medical big data. (利用医疗大数据促进合理用药)
- SEACC: Self-evolving and adaptive contrastive learning for classification of pediatric pneumonia and AP/PA chest radiographs. (SEACC：用于儿童肺炎和胸部正位/后前位X光片分类的自演化和自适应对比学习)
- Integrating retrieval-augmented generation for enhanced personalized physician recommendations in web-based medical services: model development study (将检索增强生成集成到基于网络的医疗服务中，以增强个性化医生推荐：模型开发研究)
- Energy-aware tasks offloading based on DQN in medical mobile devices (基于DQN的医疗移动设备中的节能型任务卸载)
- Early gestational diabetes mellitus risk predictor using neural network with NearMiss (基于神经网络和NearMiss的早期妊娠糖尿病风险预测模型)
- BESTMVQA: A Benchmark Evaluation System for Medical Visual Question Answering (BESTMVQA：医学视觉问答基准评估系统)
- MHGRL: An Effective Representation Learning Model for Electronic Health Records (MHGRL：一种用于电子健康记录的有效表征学习模型)
- OEHR: An Orthopedic Electronic Health Record Dataset (OEHR：骨科电子健康记录数据集)
- From A Timeline Contact Graph to Close Contact Tracing and Infection Diffusion Intervention (从时间线接触图到密切接触者追踪和感染扩散干预)
- EDRMM: enhancing drug recommendation via multi-granularity and multi-attribute representation (EDRMM：通过多粒度和多属性表示增强药物推荐)
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