Accurate assessment of thyroid cartilage invasion is crucial for treatment decision-making and prognosis evaluation in laryngeal squamous cell carcinoma (LSCC). This study aimed to compare the performance of the radiomics and deep learning (DL) model...
BACKGROUND: Accurate prediction of prognosis and risk stratification in patients with laryngeal cancer can inform appropriate treatment decision-making. This study aims to develop a multi-channel deep learning radiomics model based on contrast-enhanc...
BACKGROUND: Early diagnosis and intervention in glottic carcinoma (GC) can significantly improve long-term prognosis. However, the accurate diagnosis of early GC is challenging due to its morphological similarity to vocal cord dysplasia, with the dif...
BACKGROUND: Early-stage diagnosis of laryngeal cancer significantly improves patient survival and quality of life. However, the scarcity of specialists in low-resource settings hinders the timely review of flexible nasopharyngoscopy (FNS) videos, whi...
Journal of chemical information and modeling
Jun 9, 2025
Patients with locally advanced laryngeal and hypopharyngeal squamous cell carcinoma (LA-LHSCC) urgently need precise treatment strategies to improve the prognosis due to severe laryngeal functional impairment following traditional surgery and chemora...
BACKGROUND: Laryngeal cancer (LCA) is the second most common type of head and neck malignancy, characterized by high recurrence rates and poor overall survival (OS). However, progress in curing LCA through molecular-targeted diagnostics and therapies...
BACKGROUND: Laryngeal cancer is the second most common upper respiratory tract cancer. Early and accurate diagnosis can improve the cure rate of patients. Laryngoscopy with NBI is a commonly used tool that can help endoscopists diagnose laryngeal dis...
PURPOSE: Despite the development of diverse treatment options, there has been an increase in mortality rates for laryngeal squamous cell carcinoma (LSCC). Our research employed survival analysis and machine learning (ML) techniques to evaluate the im...
Data scarcity in medical images makes transfer learning a common approach in computer-aided diagnosis. Some disease classification tasks can rely on large homogeneous public datasets to train the transferred model, while others cannot, i.e., endoscop...
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