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Vocal Cord Paralysis

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Optimal Deep Learning-Based Vocal Fold Disorder Detection and Classification Model on High-Speed Video Endoscopy.

Journal of healthcare engineering
The use of high-speed video-endoscopy (HSV) in the study of phonatory processes linked to speech needs the precise identification of vocal fold boundaries at the time of vibration. The HSV is a unique laryngeal imaging technology that captures intrac...

Postsurgical complications after robot-assisted transaxillary thyroidectomy: critical analysis of a large cohort of European patients.

Updates in surgery
In the last decade, robot-assisted trans-axillary thyroidectomy has spread rapidly and has been proven to be a safe and effective procedure. However, several case series have reported new complications that have led to criticism regarding this approa...

A large intrathoracic goiter with tracheal stenosis: Complete resection using a robot-assisted thoracoscopic approach.

Thoracic cancer
Growing intrathoracic goiters may compress surrounding organs and deteriorate the cardiopulmonary function. Treating such cases requires carefully considering how to maintain oxygenation and resect the tumor with minimal invasiveness without complica...

Pathological Voice Detection Based on Phase Reconstitution and Convolutional Neural Network.

Journal of voice : official journal of the Voice Foundation
The nonlinear dynamic features can effectively describe the acoustic characteristics of normal and pathological voice. In this paper, the phase space reconstruction and convolution neural network are used to classify the normal and pathological voice...

Detection of Neurogenic Voice Disorders Using the Fisher Vector Representation of Cepstral Features.

Journal of voice : official journal of the Voice Foundation
Neurogenic voice disorders (NVDs) are caused by damage or malfunction of the central or peripheral nervous system that controls vocal fold movement. In this paper, we investigate the potential of the Fisher vector (FV) encoding in automatic detection...

Predictive Outcomes of Deep Learning Measurement of the Anterior Glottic Angle in Bilateral Vocal Fold Immobility.

The Laryngoscope
OBJECTIVE: (1) To compare maximum glottic opening angle (anterior glottic angle, AGA) in patients with bilateral vocal fold immobility (BVFI), unilateral vocal fold immobility (UVFI) and normal larynges (NL), and (2) to correlate maximum AGA with pat...

Deep learning in voice analysis for diagnosing vocal cord pathologies: a systematic review.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
OBJECTIVES: With smartphones and wearable devices becoming ubiquitous, they offer an opportunity for large-scale voice sampling. This systematic review explores the application of deep learning models for the automated analysis of voice samples to de...

Trust in Machine Learning Driven Clinical Decision Support Tools Among Otolaryngologists.

The Laryngoscope
BACKGROUND: Machine learning driven clinical decision support tools (ML-CDST) are on the verge of being integrated into clinical settings, including in Otolaryngology-Head & Neck Surgery. In this study, we investigated whether such CDST may influence...

Usefulness of an Artificial Intelligence Model in Recognizing Recurrent Laryngeal Nerves During Robot-Assisted Minimally Invasive Esophagectomy.

Annals of surgical oncology
BACKGROUND: Recurrent laryngeal nerve (RLN) palsy is a common complication in esophagectomy and its main risk factor is reportedly intraoperative procedure associated with surgeons' experience. We aimed to improve surgeons' recognition of the RLN dur...