AIMC Topic: Hearing Loss, Sensorineural
Clear Filters Showing 21 to 30 of 31 articles
Beyond Phecodes: leveraging PheMAP to identify patients lacking diagnosis codes in electronic health records.
Journal of the American Medical Informatics Association : JAMIA
Jun 1, 2025
OBJECTIVE: Diagnosis codes documented in electronic health records (EHR) are often relied upon to clinically phenotype patients for biomedical research. However, these diagnoses can be incomplete and inaccurate, leading to false negatives when search...
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...
A causal and talker-independent speaker separation/dereverberation deep learning algorithm: Cost associated with conversion to real-time capable operation.
The Journal of the Acoustical Society of America
Nov 1, 2021
The fundamental requirement for real-time operation of a speech-processing algorithm is causality-that it operate without utilizing future time frames. In the present study, the performance of a fully causal deep computational auditory scene analysis...
An effectively causal deep learning algorithm to increase intelligibility in untrained noises for hearing-impaired listeners.
The Journal of the Acoustical Society of America
Jun 1, 2021
Real-time operation is critical for noise reduction in hearing technology. The essential requirement of real-time operation is causality-that an algorithm does not use future time-frame information and, instead, completes its operation by the end of ...
A talker-independent deep learning algorithm to increase intelligibility for hearing-impaired listeners in reverberant competing talker conditions.
The Journal of the Acoustical Society of America
Jun 1, 2020
Deep learning based speech separation or noise reduction needs to generalize to voices not encountered during training and to operate under multiple corruptions. The current study provides such a demonstration for hearing-impaired (HI) listeners. Sen...
A deep learning algorithm to increase intelligibility for hearing-impaired listeners in the presence of a competing talker and reverberation.
The Journal of the Acoustical Society of America
Mar 1, 2019
For deep learning based speech segregation to have translational significance as a noise-reduction tool, it must perform in a wide variety of acoustic environments. In the current study, performance was examined when target speech was subjected to in...
Perceptual Effects of Adjusting Hearing-Aid Gain by Means of a Machine-Learning Approach Based on Individual User Preference.
Trends in hearing
Jan 1, 2019
This study investigated a method to adjust hearing-aid gain by use of a machine-learning algorithm that estimates the optimal setting of gain parameters based on user preference indicated in an iterative paired-comparison procedure. Twenty hearing-im...
A deep learning based segregation algorithm to increase speech intelligibility for hearing-impaired listeners in reverberant-noisy conditions.
The Journal of the Acoustical Society of America
Sep 1, 2018
Recently, deep learning based speech segregation has been shown to improve human speech intelligibility in noisy environments. However, one important factor not yet considered is room reverberation, which characterizes typical daily environments. The...
Improving the performance of hearing aids in noisy environments based on deep learning technology.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2018
The performance of a deep-learning-based speech enhancement (SE) technology for hearing aid users, called a deep denoising autoencoder (DDAE), was investigated. The hearing-aid speech perception index (HASPI) and the hearing- aid sound quality index ...
An algorithm to increase intelligibility for hearing-impaired listeners in the presence of a competing talker.
The Journal of the Acoustical Society of America
Jun 1, 2017
Individuals with hearing impairment have particular difficulty perceptually segregating concurrent voices and understanding a talker in the presence of a competing voice. In contrast, individuals with normal hearing perform this task quite well. This...
Auditory Threshold
Deep Learning
Young Adult
Hearing Loss, Sensorineural
Signal Processing, Computer-Assisted
Perceptual Masking
Humans
Hearing Aids
Correction of Hearing Impairment
Male
Signal-To-Noise Ratio
Female
Persons with Hearing Disabilities
Comprehension
Hearing
Audiometry, Speech
Middle Aged
Aged
Acoustic Stimulation
Speech Perception
Speech Intelligibility
Stay Ahead of Medical AI
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 30978
- Neural Networks, Computer 29696
- Algorithms 26813
- Deep Learning 26324
- Artificial Intelligence 24267
- Robotics 13307
- Image Processing, Computer-Assisted 9512
- Retrospective Studies 9097
- Magnetic Resonance Imaging 6173
- Reproducibility of Results 5589
- Tomography, X-Ray Computed 4765
- Support Vector Machine 4678
- Computational Biology 4229
- Brain 4045
- Computer Simulation 3877
Recent Journals
- Scientific reports 5865
- Sensors (Basel, Switzerland) 4794
- PloS one 4011
- Neural networks : the official journal of the International Neural Network Society 2928
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1839
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1278
- IEEE journal of biomedical and health informatics 1129
- Journal of chemical information and modeling 994
- Nature communications 938
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 861
- Briefings in bioinformatics 850
- IEEE transactions on neural networks and learning systems 823