Border discrimination is very important in the treatment of tongue squamous cell carcinoma
(TSCC). This study proposes an ensemble convolutional neural network (CNN) framework …

Objective To compare the real-time diagnostic accuracy of conventional white-light imaging
(WLI) endoscopy with that of narrow-band imaging (NBI) endoscopy in patients at high risk …

Background Training deep learning (DL) models to automatically recognize diseases in
nasopharyngeal MRI is a challenging task, and optimizing the performance of DL models is …

Background To build an automatic pathological diagnosis model to assess the lymph node
metastasis status of head and neck squamous cell carcinoma (HNSCC) based on deep …

METHODS: A total of 4,002 images from 1,078 patients were used to train and cross-validate
the DCNN model for diagnosing early ESCC. The performance of the model was further …

Early detection of head and neck tumors is crucial for patient survival. Often, diagnoses are
made based on endoscopic examination of the larynx followed by biopsy and histological …

Rationale and Objectives Accurate staging of laryngeal carcinoma can inform appropriate
treatment decision-making. We developed a radiomics model, a deep learning (DL) model …

Background Inverted papilloma (IP) is a common sinus neoplasm with a probability of
malignant transformation. Nasal polyps (NP) are the most frequent masses in the sinus. The …

In this work, we develop a deep learning-guided fiberoptic Raman diagnostic platform to
assess its ability of real-time in vivo nasopharyngeal carcinoma (NPC) diagnosis and post …

Objectives/Hypothesis Create an autonomous computational system to classify endoscopy
findings. Study Design Computational analysis of vocal fold images at an academic, tertiary …