Semi–Supervised vs. Supervised Learning for Mental Health Monitoring: A Case Study on Bipolar Disorder Cover

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Semi–Supervised vs. Supervised Learning for Mental Health Monitoring: A Case Study on Bipolar Disorder

International Journal of Applied Mathematics and Computer Science

Volume 33 (2023): Issue 3 (September 2023)

By: Gabriella Casalino, Giovanna Castellano, Olgierd Hryniewicz, Daniel Leite, Karol Opara, Weronika Radziszewska and Katarzyna Kaczmarek-Majer

Open Access

|Sep 2023

Authors

Gabriella Casalino

gabriella.casalino@uniba.it

Department of Computer Science, University of Bari Aldo Moro, Italy

Giovanna Castellano

Department of Computer Science, University of Bari Aldo Moro, Italy

Olgierd Hryniewicz

Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

Daniel Leite

Department of Engineering and Science, Adolfo Ibanez University, Chile

Karol Opara

Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

Weronika Radziszewska

Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

Katarzyna Kaczmarek-Majer

k.kaczmarek@ibspan.waw.pl

Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

DOI: https://doi.org/10.34768/amcs-2023-0030 | Journal eISSN: 2083-8492 | Journal ISSN: 1641-876X

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Language: English

Page range: 419 - 428

Submitted on: Nov 21, 2022

Accepted on: May 4, 2023

Published on: Sep 21, 2023

Published by: University of Zielona Góra

In partnership with: Paradigm Publishing Services

Publication frequency: 4 issues per year

Keywords:

semi-supervised learning,

mental health monitoring,

acoustic features,

pattern recognition,

Related subjects:

Applied mathematics

© 2023 Gabriella Casalino, Giovanna Castellano, Olgierd Hryniewicz, Daniel Leite, Karol Opara, Weronika Radziszewska, Katarzyna Kaczmarek-Majer, published by University of Zielona Góra
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

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