AIMC Topic: Presbycusis

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Breaking down the ear-brain dichotomy: the effects of age-related hearing loss on the cortical language system.

NeuroImage
Older individuals frequently experience hearing difficulties, often due to sensorineural hearing loss (HL) primarily originating in the inner ear. However, it is not uncommon for older adults with HL to also exhibit impairments in speech intelligibil...

A machine-learning-based approach to predict early hallmarks of progressive hearing loss.

Hearing research
Machine learning (ML) techniques are increasingly being used to improve disease diagnosis and treatment. However, the application of these computational approaches to the early diagnosis of age-related hearing loss (ARHL), the most common sensory def...

Identifying a gene signature for age-related hearing loss through machine learning and revealing the effect of the CTSS on the mice cochlea.

Biogerontology
Age-related hearing loss (ARHL) is one of the most common health conditions among the elderly population. This study used machine learning to screen for a gene signature to predicts ARHL. Four ARHL mice cochlear transcriptome datasets and the mRNA se...

Machine Learning Models Can Predict Tinnitus and Noise-Induced Hearing Loss.

Ear and hearing
OBJECTIVES: Despite the extensive use of machine learning (ML) models in health sciences for outcome prediction and condition classification, their application in differentiating various types of auditory disorders remains limited. This study aimed t...

Machine learning reveal shared diagnostic biomarkers and convergent pathways in age-related hearing loss and sarcopenia.

Medicine
Age-related hearing loss (HL) and sarcopenia (ARS) are prevalent geriatric syndromes sharing common risk factors. This study aimed to identify shared biomarkers and elucidate convergent pathogenic mechanisms. Transcriptomic datasets were obtained fro...

A model of speech recognition for hearing-impaired listeners based on deep learning.

The Journal of the Acoustical Society of America
Automatic speech recognition (ASR) has made major progress based on deep machine learning, which motivated the use of deep neural networks (DNNs) as perception models and specifically to predict human speech recognition (HSR). This study investigates...