AI Medical Compendium Topic

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Nasal Cavity

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A Haptic Guided Robotic System for Endoscope Positioning and Holding.

Turkish neurosurgery
AIM: To determine the feasibility, advantages, and disadvantages of using a robot for holding and maneuvering the endoscope in transnasal transsphenoidal surgery.

Foot-controlled robotic-enabled endoscope holder for endoscopic sinus surgery: A cadaveric feasibility study.

The Laryngoscope
OBJECTIVES/HYPOTHESIS: To evaluate the feasibility of a unique prototype foot-controlled robotic-enabled endoscope holder (FREE) in functional endoscopic sinus surgery.

Machine learning-based prediction of outcomes of the endoscopic endonasal approach in Cushing disease: is the future coming?

Neurosurgical focus
OBJECTIVE: Machine learning (ML) is an innovative method to analyze large and complex data sets. The aim of this study was to evaluate the use of ML to identify predictors of early postsurgical and long-term outcomes in patients treated for Cushing d...

Feasibility of a deep learning-based algorithm for automated detection and classification of nasal polyps and inverted papillomas on nasal endoscopic images.

International forum of allergy & rhinology
BACKGROUND: Discrimination of nasal cavity mass lesions is a challenging work requiring extensive experience. A deep learning-based automated diagnostic system may help clinicians to classify nasal cavity mass lesions. We demonstrated the feasibility...

Exploring the influence of nasal vestibule structure on nasal obstruction using CFD and Machine Learning method.

Medical engineering & physics
Motivated by clinical findings about the nasal vestibule, this study analyzes the aerodynamic characteristics of the nasal vestibule and attempt to determine anatomical features which have a large influence on airflow through a combination of Computa...

Deep learning algorithm for the automated detection and classification of nasal cavity mass in nasal endoscopic images.

PloS one
Nasal endoscopy is routinely performed to distinguish the pathological types of masses. There is a lack of studies on deep learning algorithms for discriminating a wide range of endoscopic nasal cavity mass lesions. Therefore, we aimed to develop an ...

Deep learning model for differentiating nasal cavity masses based on nasal endoscopy images.

BMC medical informatics and decision making
BACKGROUND: Nasal polyps and inverted papillomas often look similar. Clinically, it is difficult to distinguish the masses by endoscopic examination. Therefore, in this study, we aimed to develop a deep learning algorithm for computer-aided diagnosis...

Comparative analysis of the human microbiome from four different regions of China and machine learning-based geographical inference.

mSphere
The human microbiome, the community of microorganisms that reside on and inside the human body, is critically important for health and disease. However, it is influenced by various factors and may vary among individuals residing in distinct geographi...