Lesica, NA;
Mehta, N;
Manjaly, JG;
Deng, L;
Wilson, BS;
Zeng, F-G;
(2021)
Harnessing the power of artificial intelligence to transform hearing healthcare and research.
Nature Machine Intelligence
, 3
(10)
pp. 840-849.
10.1038/s42256-021-00394-z.
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Abstract
The advances in artificial intelligence that are transforming many fields have yet to make an impact in hearing. Hearing healthcare continues to rely on a labour-intensive service model that fails to provide access to the majority of those in need, while hearing research suffers from a lack of computational tools with the capacity to match the complexities of auditory processing. This Perspective is a call for the artificial intelligence and hearing communities to come together to bring about a technological revolution in hearing. We describe opportunities for rapid clinical impact through the application of existing technologies and propose directions for the development of new technologies to create true artificial auditory systems. There is an urgent need to push hearing towards a future in which artificial intelligence provides critical support for the testing of hypotheses, the development of therapies and the effective delivery of care worldwide.
| Type: | Article |
|---|---|
| Title: | Harnessing the power of artificial intelligence to transform hearing healthcare and research |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1038/s42256-021-00394-z |
| Publisher version: | https://doi.org/10.1038/s42256-021-00394-z |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > The Ear Institute |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10137247 |
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