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JuryFlow is presented, a disagreement-guided, human-in-the-loop multi-agent evaluation framework that treats inter-judge disagreement not as noise to be averaged away, but as a precise, claim-level signal indicating where an evaluation is uncertain.
Identifying synergistic anti-cancer drug combinations is crucial for improving efficacy and reducing toxicity, but exhaustive experimental screening is prohibitively costly. We present SYNAPX, an explainable deep learning framework for drug synergy prediction that integrates chemical features of drug pairs with gene ex...
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