A multi-agent LLM framework with safety-oriented reasoning gates improves diagnostic accuracy and must-not-miss condition coverage over standalone LLMs across case-report benchmarks and a blinded physician evaluation of 43 real-world ED notes.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.AI 1years
2026 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
A safety-oriented hypothetico-deductive framework for AI-assisted differential diagnosis
A multi-agent LLM framework with safety-oriented reasoning gates improves diagnostic accuracy and must-not-miss condition coverage over standalone LLMs across case-report benchmarks and a blinded physician evaluation of 43 real-world ED notes.