aceFrom 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…
In a prospective silent trial, a hematology AI agent matched tumor-board decisions about 83% of the time, with hallucinations in 0.3% of cases.
Sources
- Peer-reviewedTurkish Journal of Hematology2026-09-21
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Truvace Impact Record TRV-2026-1168, v3: “From Answers to Agents: What Must Change Before Generative and Agentic AI Become Clinical Infrastructure in Hematology.” Truvace, 2026-11-04. /record/TRV-2026-1168 (accessed on the day you copy it). sha256 fc0ba415559f0ef6…
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