AIMC Topic: Hearing Loss, Sudden
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Prediction of hearing recovery with deep learning algorithm in sudden sensorineural hearing loss.
Scientific reports
Aug 29, 2024
This study aimed to establish a deep learning-based predictive model for the prognosis of idiopathic sudden sensorineural hearing loss (SSNHL). Data from 1108 patients with SSNHL between January 2015 and May 2023 were retrospectively analyzed. Patien...
Three-dimensional heavily T2-weighted FLAIR in the detection of blood-labyrinthine barrier leakage in patients with sudden sensorineural hearing loss: comparison with T1 sequences and application of deep learning-based reconstruction.
European radiology
Jan 17, 2024
OBJECTIVE: Blood-labyrinthine barrier leakage has been reported in sudden sensorineural hearing loss (SSNHL). We compared immediate post-contrast 3D heavily T2-weighted fluid-attenuated inversion recovery (FLAIR), T1 spin echo (SE), and 3D T1 gradien...
Machine Learning Models for Predicting Sudden Sensorineural Hearing Loss Outcome: A Systematic Review.
The Annals of otology, rhinology, and laryngology
Oct 20, 2023
BACKGROUND: Machine Learning models have been applied in various healthcare fields, including Audiology, to predict disease outcomes. The prognosis of sudden sensorineural hearing loss is difficult to predict due to the variable course of the disease...
Artificial Neural Network-Assisted Classification of Hearing Prognosis of Sudden Sensorineural Hearing Loss With Vertigo.
IEEE journal of translational engineering in health and medicine
Feb 6, 2023
This study aimed to determine the impact on hearing prognosis of the coherent frequency with high magnitude-squared wavelet coherence (MSWC) in video head impulse test (vHIT) among patients with sudden sensorineural hearing loss with vertigo (SSNHLV)...
Predicting hearing recovery following treatment of idiopathic sudden sensorineural hearing loss with machine learning models.
American journal of otolaryngology
Jan 4, 2021
PURPOSE: Idiopathic sudden sensorineural hearing loss (ISSHL) is an emergency otological disease, and its definite prognostic factors remain unclear. This study applied machine learning methods to develop a new ISSHL prognosis prediction model.
Predicting the hearing outcome in sudden sensorineural hearing loss via machine learning models.
Clinical otolaryngology : official journal of ENT-UK ; official journal of Netherlands Society for Oto-Rhino-Laryngology & Cervico-Facial Surgery
Feb 20, 2018
OBJECTIVE: Sudden sensorineural hearing loss (SSHL) is a multifactorial disorder with high heterogeneity, thus the outcomes vary widely. This study aimed to develop predictive models based on four machine learning methods for SSHL, identifying the be...
[Evaluation of effect of acupuncture and moxibustion and level of intervention based on cumulative Meta-analysis and fuzzy comprehensive evaluation:sudden hearing loss].
Zhongguo zhen jiu = Chinese acupuncture & moxibustion
Jul 12, 2016
Clinical evidences of acupuncture and moxibustion for sudden hearing loss(SHL) were completely collected, and the quality of the evidences was evaluated by Jadad scale. Cumulative Meta-analysis and the time tendency test for the results were implemen...
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