AIMC Topic: Nose Diseases

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NaMA-Mamba: Foundation model for generalizable nasal disease detection using masked autoencoder with Mamba on endoscopic images.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Mar 12, 2025
Artificial intelligence (AI) has shown great promise in analyzing nasal endoscopic images for disease detection. However, current AI systems require extensive expert-labeled data for each specific medical condition, limiting their applications. In th...
Humans Artificial Intelligence Machine Learning Algorithms Endoscopy Image Interpretation, Computer-Assisted Autoencoder Nose Diseases
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An artificial intelligence algorithm that identifies middle turbinate pneumatisation (concha bullosa) on sinus computed tomography scans.

The Journal of laryngology and otology Apr 1, 2020
OBJECTIVE: Convolutional neural networks are a subclass of deep learning or artificial intelligence that are predominantly used for image analysis and classification. This proof-of-concept study attempts to train a convolutional neural network algori...
Humans Neural Networks, Computer Artificial Intelligence Algorithms Retrospective Studies Tomography, X-Ray Computed Female Male Australia Paranasal Sinuses Observer Variation Nose Diseases Turbinates
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HypernasalityNet: Deep recurrent neural network for automatic hypernasality detection.

International journal of medical informatics May 23, 2019
BACKGROUND: Cleft palate patients have inability to produce adequate velopharyngeal closure, which results in hypernasal speech. In clinic, hypernasal speech is assessed through subject assessment by speech language pathologists. Automatic hypernasal...
Humans Neural Networks, Computer Female Male Speech Adolescent Child, Preschool Child Cleft Palate Nose Diseases
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