Transitioning to AI-Based Laryngeal Cancer Diagnosis: A Systematic Review

Abstract

Difficulty with speech, respiration, and deglutition represents a primary clinical presentation in patients diagnosed with laryngeal cancer.Accounting for approximately 1.1 million cases globally, this head and neck malignancy directly impairs the structural and functional integrity of the larynx.Conventional diagnostic and treatment modalities rely heavily on specialized otolaryngological expertise and often carry risks of collateral tissue damage or compromised functional preservation.To mitigate these clinical constraints, artificial intelligence (AI) methodologies have emerged as prominent tools for enabling early detection and precision diagnosis.This systematic review synthesizes literature published between January 2011 and April 2026, mapping the evolutionary trajectory and recent advancements of AI applications in laryngeal oncology.Following PRISMA guidelines, relevant literature was systematically selected and evaluated to highlight methodological developments, identify current clinical limitations, and delineate existing research gaps.