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Facial Paralysis

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Feasibility of using the postauricular-groove approach without endoscopic assistant for excision of parotid tumors. Results from a series of 58 cases.

Journal of cranio-maxillo-facial surgery : official publication of the European Association for Cranio-Maxillo-Facial Surgery
The aim of the study was to evaluate the efficacy and preliminary outcomes of using a postauricular-groove approach without endoscopic assistance for the excision of parotid tumors. Patients who underwent parotidectomy using a postauricular-groove in...

Deep Learning-Based Surface Nerve Electromyography Data of E-Health Electroacupuncture in Treatment of Peripheral Facial Paralysis.

Computational and mathematical methods in medicine
This study was aimed at exploring the application value of electroacupuncture in the treatment of peripheral facial palsy using surface nerve electromyogram (EMG) image data based on deep learning. The surface nerve EMG recognition model was construc...

Classification of facial paralysis based on machine learning techniques.

Biomedical engineering online
Facial paralysis (FP) is an inability to move facial muscles voluntarily, affecting daily activities. There is a need for quantitative assessment and severity level classification of FP to evaluate the condition. None of the available tools are widel...

Automatic grading of patients with a unilateral facial paralysis based on the Sunnybrook Facial Grading System - A deep learning study based on a convolutional neural network.

American journal of otolaryngology
PURPOSE: In order to assess the severity and the progression of a unilateral peripheral facial palsy the Sunnybrook Facial Grading System (SFGS) is a well-established grading system due to its clinical relevance, sensitivity, and robust measuring met...

Assessing facial weakness in myasthenia gravis with facial recognition software and deep learning.

Annals of clinical and translational neurology
OBJECTIVE: Myasthenia gravis (MG) is an autoimmune disease leading to fatigable muscle weakness. Extra-ocular and bulbar muscles are most commonly affected. We aimed to investigate whether facial weakness can be quantified automatically and used for ...

Deep Learning for the Assessment of Facial Nerve Palsy: Opportunities and Challenges.

Facial plastic surgery : FPS
Automated evaluation of facial palsy using machine learning offers a promising solution to the limitations of current assessment methods, which can be time-consuming, labor-intensive, and subject to clinician bias. Deep learning-driven systems have t...

Artificial Intelligence-Based Facial Palsy Evaluation: A Survey.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Facial palsy evaluation (FPE) aims to assess facial palsy severity of patients, which plays a vital role in facial functional treatment and rehabilitation. The traditional manners of FPE are based on subjective judgment by clinicians, which may ultim...

Optimization of the automated Sunnybrook Facial Grading System - Improving the reliability of a deep learning network with facial landmarks.

European annals of otorhinolaryngology, head and neck diseases
OBJECTIVE: The Sunnybrook Facial Grading System (SFGS) is a well-established grading system to assess the severity and progression of a unilateral facial palsy. The automation of the SFGS makes the SFGS more accessible for researchers, students, clin...

Applications of artificial intelligence in facial plastic and reconstructive surgery: a systematic review.

Current opinion in otolaryngology & head and neck surgery
PURPOSE OF REVIEW: Arguably one of the most disruptive innovations in medicine of the past decade, artificial intelligence is dramatically changing how healthcare is practiced today. A systematic review of the most recent artificial intelligence adva...

Dynamic blinking feature extraction for automated facial nerve paralysis detection.

Computers in biology and medicine
Facial nerve paralysis (FNP) impair eyelid closure and blinking, risking ophthalmic complications and vision loss. Current detection methods primarily rely on static facial asymmetries, overlooking the dynamic eyelid movements during blinking that ar...