Researchers have developed SCOPE-AD, a novel sequential planning agent designed for cost-aware diagnosis of Alzheimer's disease. This agent utilizes an ordinal-belief model to represent uncertainty across the spectrum from cognitively normal to mild cognitive impairment and Alzheimer's disease. By learning from sampled Bellman targets and distilling action distributions into a Qwen policy, SCOPE-AD selectively decides which diagnostic tests to acquire and when to make a diagnosis, considering budget and patient burden constraints. On the ADNI dataset, SCOPE-AD achieved a Macro-F1 score of 77.70% at an average acquisition cost of $50.46, significantly outperforming baseline methods and demonstrating the value of selective evidence acquisition for cost-effective diagnosis. AI
IMPACT This research could lead to more cost-effective and efficient diagnostic pathways for Alzheimer's disease.
RANK_REASON This is a research paper detailing a novel AI agent for a specific diagnostic task. [lever_c_demoted from research: ic=1 ai=1.0]
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