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Submitted: 12 February 2025 You are already at the latest version Fermentations are complex and often unpredictable processes. However, fermentation-based bioprocesses generate large volumes of data that are currently underexplored. These data can be used to develop data-driven models, such as machine learning (ML), to improve process predictability. Among various fermentation products, biosurfactants have emerged as promising candidates for several industrial applications.
5. Discussion The results of our study suggest that coupling a trained encoder with a classifier can effectively distinguish NSR from AFib waveforms using single-lead ECG recordings. The Supervised AEs demonstrated the ability to create a feature space that enhanced the classification performance, outperforming the “unsupervised” versions (Table 4). This is also supported by the lower train and validation losses (Figure 9, Figure 10 and Figure 11).
This is an early access version, the complete PDF, HTML, and XML versions will be available soon. Open AccessArticle by Afonso Fortes Ferreira 1,2, Hugo Plácido da Silva 1,2,*, Helena Alves 1,3, Nuno Marques 4 and Ana Fred 1,2 1 Instituto Superior Técnico (IST), Av. Rovisco Pais n. 1, 1049-001 Lisboa, Portugal 2 Instituto de Telecomunicações (IT), Av. Rovisco Pais n.
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