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Behavioral pattern analysis for adherence in clinical trials using sequence mining
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DOI：10.1016/j.compbiomed.2026.111607.png)
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Abstract
En 中文
• We transform raw clinical visit logs into behavioral sequences for adherence analysis. • cSPADE sequence mining identifies patterns linked to both dropout and completion. • Event encoding merges visit type, rescheduling, and timing into interpretable tokens. • Sunburst visualizations reveal subgroup trajectories and distinct risk behaviors. • The framework supports decision-making in resource-limited clinical trial settings. • Repeated rescheduling and visit modality predict dropout, highlighting high-risk groups.
Keywords:
Clinical trials
Sequence mining
Adherence
Behavioral patterns
cSPADE
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