信息管理与商业智能系学术讲座（4月7日）
题目：A Distribution-Wise Temporal Multimodal Learning Approach for Disease Progression Assessment
主讲人：李文文 副教授 信息管理与商业智能系
时间：2026-04-07 13:30-14:30
地点：李达三楼105室
内容摘要:The rise of mobile health technologies has expanded opportunities for chronic disease management by enabling healthcare assessment, intervention, and delivery through smartphones and wearables. Yet, assessing chronic disease progression from patient-centric mobile data faces three key challenges, including integrating multimodal data, analyzing long-term data with irregular time intervals, and ensuring interpretability with reliable uncertainty estimates. Guided by the design science paradigm and grounded in the dynamic symptoms model, we propose distribution-wise temporal multimodal learning (DTML) for progression prediction. Using a publicly available smartphone dataset, we demonstrate that DTML outperforms state-of-the-art benchmarks in early-stage disease progression assessment. We also present a case study and additional analyses to discuss insights and practical implications. This study contributes to the design of IT artifacts for mobile health and extends symptom management theory, offering actionable implications for healthcare stakeholders.
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