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.
|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
|Conference||Machine Learning for Healthcare|
|Period||21/11/22 → 21/11/22|
Bibliographical noteWinner of the Best Poster Award.
- machine learning
- COVID-19 classification
- imbalanced data