Interactive LLM dialogue raised residents' hard-case diagnostic correctness from 0.589 to 0.734 and produced medium effect sizes in a blinded study of seven physicians on 52 emergency cases.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
years
2026 2verdicts
UNVERDICTED 2roles
background 1polarities
background 1representative citing papers
MedThink, a two-stage teacher-guided reasoning correction distillation framework, boosts small language models' medical diagnostic accuracy by up to 12.7% on benchmarks and achieves 56.4% on a gastroenterology dataset.
citing papers explorer
-
Human-LLM Dialogue Improves Diagnostic Accuracy in Emergency Care
Interactive LLM dialogue raised residents' hard-case diagnostic correctness from 0.589 to 0.734 and produced medium effect sizes in a blinded study of seven physicians on 52 emergency cases.
-
MedThink: Enhancing Diagnostic Accuracy in Small Models via Teacher-Guided Reasoning Correction
MedThink, a two-stage teacher-guided reasoning correction distillation framework, boosts small language models' medical diagnostic accuracy by up to 12.7% on benchmarks and achieves 56.4% on a gastroenterology dataset.