Machine learning in personalized laryngeal cancer management: insights into clinical characteristics, therapeutic options, and survival predictions.

Purpose: Over the last 40 years, there has been an unusual trend where, even though there are more varied treatments, survival rates have not improved much. Our study used survival analysis and machine learning (ML) to investigate this odd situation and to improve prediction methods for treating non-metastatic LSCC.

Methods: The surveillance, epidemiology and end results (SEER) database provided the data used for this study's analysis.