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Related Experiment Video

Updated: Jul 12, 2025

Neuro-rehabilitation Approach for Sudden Sensorineural Hearing Loss

Neuro-rehabilitation Approach for Sudden Sensorineural Hearing Loss

Published on: January 25, 2016

Machine Learning Models for Predicting Sudden Sensorineural Hearing Loss Outcome: A Systematic Review.

Amirhossein Aghakhani¹, Milad Yousefi², Mir Saeed Yekaninejad¹

¹Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.

The Annals of Otology, Rhinology, and Laryngology

|October 21, 2023

Summary

Machine learning models show promise for predicting sudden sensorineural hearing loss outcomes. However, high bias in current studies limits their real-world applicability, requiring further validation.

Keywords:

audiology machine learning sudden hearing loss systematic review

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Last Updated: Jul 12, 2025

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Published on: October 26, 2019

Area of Science:

Audiology and healthcare informatics
Biomedical data science

Background:

Sudden sensorineural hearing loss (SSNHL) prognosis is challenging due to disease variability.
Machine learning (ML) models are increasingly used in healthcare for outcome prediction.
Predicting SSNHL outcomes with ML is an active area of research.

Conclusions:

ML models demonstrate promising performance for SSNHL prediction.
High risk of bias raises concerns about current model applicability in clinical practice.
Future research needs multi-cohort studies, varied feature selection, and external validation.