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TRV-2026-1168Certified recordPeer-reviewed

From Answers to Agents: What Must Change Before Generative and Agentic AI Become Clinical Infrastructure in Hematology

Generative artificial intelligence in hematology is entering a new phase. The dominant question, whether large language models are accurate enough for clinical decision support, is being overtaken by a harder one, as systems shift from answering questions to acting: extracting structured cases, routing them, classifying variants, and grounding recommendations in guidelines and case memory. In 2026, a hematology agent achieved roughly 83% concordance with tumor-board decisions in a prospective silent trial, with…

Health · P Space — documented harm · certified 2026-09-22 · v1 · article view · machine-readable

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From Answers to Agents: What Must Change Before Generative and Agentic AI Become Clinical Infrastructure in Hematology: In 2026, a hematology agent achieved roughly 83% concordance with tumor-board decisions in a prospective silent trial, with hallucinations in 0.3%, suggesting that for well-structured tasks the binding constraint is shifting from accuracy to governability.

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Truvace Impact Record TRV-2026-1168, v1: “From Answers to Agents: What Must Change Before Generative and Agentic AI Become Clinical Infrastructure in Hematology.” Truvace, 2026-09-22. /record/TRV-2026-1168 (accessed at citation time). sha256 588383241407bfcb…

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