Our research demonstrates that convolutional neural networks can significantly enhance the precision of nasal endoscopy interpretation. Achieving an average accuracy of 91.5% in localizing essential ...
A team of researchers from Ochsner Health recently published an insightful article in the International Forum of Allergy & Rhinology exploring the application of convolutional neural networks (CNNs) ...
Nasal endoscopy (NE) is an essential diagnostic tool in rhinology, but its effectiveness can be hampered by the complex structure of the nasal cavity. The study investigated a CNN-based model designed ...
Endoscopic medial maxillectomy is currently the most commonly used endoscopic approach to the maxillary sinus inverting papilloma. The possible complications of this procedure include epiphora, ...
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