dailyai.report

The PathoSage framework separates knowledge retrieval, evidence collection, and adjudication into three distinct stages. This architecture prevents context contamination by independently evaluating heterogeneous tool outputs. It targets patch-level reasoning in computational pathology where standard MLLMs often hallucinate morphological features. Practitioners gain a more reliable method for adjudicating conflicting evidence in medical imaging.