AIMC Topic: Hearing Loss
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The design and validation of a hybrid digital-signal-processing plug-in for traditional cochlear implant speech processors.
Computer methods and programs in biomedicine
Mar 12, 2018
BACKGROUND AND OBJECTIVE: Cochlear implants (CIs) are electronic devices restoring partial hearing to deaf individuals with profound hearing loss. In this paper, a new plug-in for traditional IIR filter-banks (FBs) is presented for cochlear implants ...
Cascade recurring deep networks for audible range prediction.
BMC medical informatics and decision making
May 18, 2017
BACKGROUND: Hearing Aids amplify sounds at certain frequencies to help patients, who have hearing loss, to improve the quality of life. Variables affecting hearing improvement include the characteristics of the patients' hearing loss, the characteris...
Fractionated stereotactic radiation therapy for vestibular schwannomas: Dosimetric factors predictive of hearing outcomes.
Practical radiation oncology
Dec 3, 2015
PURPOSE: To determine dosimetric factors predictive of hearing loss in vestibular schwannoma (VS) patients treated with definitive fractionated stereotactic radiation therapy (FSRT), and to report tumor control, serviceable hearing preservation, and ...
Towards Investigating Residual Hearing Loss: Quantification of Fibrosis in a Novel Cochlear OCT Dataset.
IEEE transactions on bio-medical engineering
Jul 1, 2025
OBJECTIVE: Cochlear implants (CIs) are bionic prostheses that restores hearing via electrical stimulation of the auditory nerve. Hybrid CIs, which use electroacoustic stimulation (EAS), combine residual low-frequency acoustic hearing with CI electric...
Machine learning-based prediction of hearing loss: Findings of the US NHANES from 2003 to 2018.
Hearing research
Jun 1, 2025
The prevalence of hearing loss (HL) has emerged as an escalating public health concern globally. The objective of this study was to leverage data from the National Health and Nutritional Examination Survey (NHANES) to develop an interpretable predict...
Piezoelectric nanofiber-based intelligent hearing system.
Science advances
May 9, 2025
Hearing loss, affecting individuals of all ages, can impair education, social function, and quality of life. Current treatments, such as hearing aids and implants, aim to mitigate these effects but often fall short in addressing the critical issue of...
Deep learning-based classification of speech disorder in stroke and hearing impairment.
PloS one
Jan 1, 2025
BACKGROUND AND OBJECTIVE: Speech disorders can arise from various causes, including congenital conditions, neurological damage, diseases, and other disorders. Traditionally, medical professionals have used changes in voice to diagnose the underlying ...
Using deep learning to improve the intelligibility of a target speaker in noisy multi-talker environments for people with normal hearing and hearing loss.
The Journal of the Acoustical Society of America
Jul 1, 2024
Understanding speech in noisy environments is a challenging task, especially in communication situations with several competing speakers. Despite their ongoing improvement, assistive listening devices and speech processing approaches still do not per...
Performance and Reliability Evaluation of an Automated Bone-Conduction Audiometry Using Machine Learning.
Trends in hearing
Jan 1, 2024
To date, pure-tone audiometry remains the gold standard for clinical auditory testing. However, pure-tone audiometry is time-consuming and only provides a discrete estimate of hearing acuity. Here, we aim to address these two main drawbacks by develo...
Progress made in the efficacy and viability of deep-learning-based noise reduction.
The Journal of the Acoustical Society of America
May 1, 2023
Recent years have brought considerable advances to our ability to increase intelligibility through deep-learning-based noise reduction, especially for hearing-impaired (HI) listeners. In this study, intelligibility improvements resulting from a curre...
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