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Navigating Oral Cancer Management: Combining Artificial Intelligence and Clinical Guidelines for Optimal
Mario Augusto Ferrari de Castro1, Rogério Aparecido Dedivitis2, Leandro Luongo de Matos3
1Metropolitan University of Santos, Santos, Brazil.
International Archives of Otorhinolaryngology
|August 15, 2026
Summary
Large language models (LLMs) show 75% accuracy when assisting surgical decision-making for advanced oral cancer, aligning with clinical guidelines. These AI tools can complement existing medical recommendations.
Area of Science:
- Medical Informatics
- Artificial Intelligence in Surgery
- Oncology Decision Support
Background:
- Surgical decision-making is complex and critical.
- Artificial Intelligence (AI) is increasingly used to support clinical decisions.
- Limited research exists on AI's impact on surgical decision-making.
Purpose of the Study:
- To assess the accuracy of AI in guiding clinical decisions for advanced oral cancer treatment.
- To compare AI-generated responses with established clinical guidelines.
Main Methods:
- Formulated structured questions based on seven clinical recommendations.
- Processed questions through multiple large language model (LLM) platforms.
- Assessed LLM responses for congruence with guidelines and clinical significance by subject matter experts.
Main Results:
- 75% of LLM responses (21 out of 28) aligned with clinical guidelines.
- Three LLM responses were contradictory to guidelines.
- Guidelines offered more comprehensive information in three instances, while one LLM provided additional relevant data.
Conclusions:
- LLMs achieved 75% concordance with established clinical guidelines.
- AI tools demonstrate potential as complementary resources for surgical decision-making.
- Further research is needed to fully integrate AI into surgical practice.
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