Background Laryngeal squamous cell carcinoma (LSCC) is one of the most common tumors
of the respiratory tract. Currently, the diagnosis of LSCC is mainly based on a laryngoscopy …

Objective To develop a deep convolutional neural network (DCNN) that can automatically
detect laryngeal cancer (LCA) in laryngoscopic images. Methods A DCNN-based diagnostic …

Objectives/Hypothesis To develop a deep‐learning‐based automatic diagnosis system for
identifying nasopharyngeal carcinoma (NPC) from noncancer (inflammation and …

Background Laryngopharyngeal cancer (LPC) includes laryngeal and hypopharyngeal
cancer, whose early diagnosis can significantly improve the prognosis and quality of life of …

Objectives/Hypothesis To develop a deep‐learning–based computer‐aided diagnosis
system for distinguishing laryngeal neoplasms (benign, precancerous lesions, and cancer) …

Objectives The prognosis for pharyngeal cancer is relatively poor. It is usually diagnosed in
an advanced stage. Although the recent development of narrow‐band imaging (NBI) and …

Laryngeal cancer is one of the most common malignant tumors in otolaryngology, and
histopathological image analysis is the gold standard for the diagnosis of laryngeal cancer …

The pathologic diagnosis of nasopharyngeal carcinoma (NPC) by different pathologists is
often inefficient and inconsistent. We have therefore introduced a deep learning algorithm …

Squamous cell carcinoma (SCC) is one of the most common as well as deadliest kinds of
laryngeal cancer. The precise and early identification of laryngeal cancer plays a pivotal role …

Background There are no published reports evaluating the ability of artificial intelligence (AI)
in the endoscopic diagnosis of superficial laryngopharyngeal cancer (SLPC). We presented …