Uncertainty-Guided Latent Diagnostic Trajectory Learning for Sequential Clinical Diagnosis

ArXi:2604.05116v1 Announce Type: new Clinical diagnosis requires sequential evidence acquisition under uncertainty. However, most Large Language Model (LLM) based diagnostic systems assume fully observed patient information and. therefore. do not explicitly model how clinical evidence should be sequentially acquired over time. Even when diagnosis is formulated as a sequential decision process, it is still challenging to learn effective diagnostic trajectories.