Abstract
Hypopharyngeal carcinoma (HPC) has one of the poorest prognoses among all types of head and neck squamous cell carcinoma (HNSCC). Artificial intelligence (AI) is a scientific field that is in the spotlight, especially in the last decade, and AI has also been widely used in the research field of HPC. This scoping review aimed to describe the improvement of HPC clinical cares brought by AI. Literatures utilizing AI and machine learning in HPC were searched in PubMed, EMBASE, and Web of Science, and 116 articles from 1987 to 2024 were retrieved. After removing duplicate and irrelevant articles, 85 were further selected for detailed review. AI helps analyze large amounts of data from HPC patients and develop models to facilitate clinical practice. The emergence of AI improves the endoscopic, radiologic, and pathologic diagnosis accuracy of HPC and guides personalized treatment and prognosis prediction. However, there are certain unmet challenges that need to be further elucidated, like interpreting the AI algorithms into features that can be observed by humans and promoting the AI models in larger and multi-centered cohorts.