Abstract
COVID cough data is heavily imbalanced, and it is challenging to collect more samples. Therefore, models are biased and their predictions cannot be trusted. In this poster, we propose a confidence measure for COVID-19 cough classification.
Original language | English |
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Number of pages | 1 |
Publication status | Published - 21 Nov 2022 |
Event | Machine Learning for Healthcare - Institute of Physics, London, United Kingdom Duration: 21 Nov 2022 → 21 Nov 2022 https://iop.eventsair.com/mlh2022/ |
Conference
Conference | Machine Learning for Healthcare |
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Abbreviated title | MLH |
Country/Territory | United Kingdom |
City | London |
Period | 21/11/22 → 21/11/22 |
Internet address |
Bibliographical note
Winner of the Best Poster Award.Keywords
- machine learning
- COVID-19 classification
- imbalanced data