Real-world diagnostic and management decisions in rhinology by a large language model: a retrospective study.
AI language models offer clinically reasonable diagnostic suggestions in specialty ear, nose, and throat care, supporting future clinical decision support.
LLM-generated diagnostic and management decisions in rhinology show concordance with clinical practice in a real-world retrospective evaluation, demonstrating AI-assisted clinical decision support feasibility in specialty ENT settings. This record was retained from the prior triage attempt for PubMed pipeline handoff.
What the study was
- Study design
- retrospective_study
- Category
- ai_diagnostics
- Maturity
- Validated
- Journal
- European Archives of Oto-Rhino-Laryngology
Why it surfaced
LLM clinical decision support in rhinology; real-world AI evaluation relevant to AI-diagnostics pipeline and specialty medicine automation.
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