Oct 1, 2019 · Cochlear implants (CI) are a unique fit for machine learning techniques given the need for optimization of signal processing to fit complex environmental scenarios and …

Simulating speech processing with cochlear implants: How does channel interaction affect learning in neural networks? PLoS ONE 14 (2): e0212134. …

Aug 14, 2024 · Predicting Postoperative Cochlear Implant Performance Using Supervised Machine Learning. Otol Neurotol. 2020 Sep;41(8):e1013-e1023. doi: …

Dec 1, 2021 · This system records the complex bipolar impedance of eight electrode pairs sequentially during the automated insertion and detects the direction it is being inserted from …

We used a data-driven multivariate approach based on machine learning to evaluate postoperative hearing and speech rehabilitation in patients with CND and the influencing factors.

We present a hybrid approach where convolutional neural networks are combined with computational neuroscience to yield a real-time end-to-end model for human cochlear …

The current study aimed to evaluate the efficacy of utilizing a machine learning-based strategy to mitigate the effects of reverberation and background noise in CIs. The strategy was tested on …

Apr 4, 2025 · This study aims to evaluate the ability of ML to predict speech perception performance among CI recipients at 6-month post-implantation using only preoperative …

Feb 1, 2024 · Toolbox for simulating cochlear implant signal processing and its effects on sound as heard by the implant recipient. A Jupyter Notebook displaying an overview of different …

Feb 27, 2019 · Simulating speech processing with cochlear implants: How does channel interaction affect learning in neural networks? We introduce a novel machine learning …