Post-stroke respiratory complications using machine learning with voice features from mobile devices
Abstract Abnormal voice may identify those at risk of post-stroke aspiration. This study was aimed to determine whether machine learning algorithms with voice recorded via a mobile device can accurately classify those with dysphagia at risk of tube feeding and post-stroke aspiration pneumonia and be...
Main Authors: | Hae-Yeon Park, DoGyeom Park, Hye Seon Kang, HyunBum Kim, Seungchul Lee, Sun Im |
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Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2022-10-01
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Series: | Scientific Reports |
Online Access: | https://doi.org/10.1038/s41598-022-20348-8 |
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