Zobrazeno 1 - 10
of 75
pro vyhledávání: '"Nikolaidis Konstantinos"'
Autor:
Baumgardt Johanna, Schwarz Julian, Bechdolf Andreas, Nikolaidis Konstantinos, Heinze Martin, Hamann Johannes, Holzke Martin, Längle Gerhard, Richter Janina, Brieger Peter, Kilian Reinhold, Timm Jürgen, Hirschmeier Constance, Von Peter Sebastian, Weinmann Stefan
Publikováno v:
BMC Psychiatry, Vol 21, Iss 1, Pp 1-13 (2021)
Abstract Background Over the last decades, many high-income countries have successfully implemented assertive outreach mental health services for acute care. Despite evidence that these services entail several benefits for service users, Germany has
Externí odkaz:
https://doaj.org/article/9958cea23e414c2c82aaac7104ac4a46
Autor:
Kristiansen, Stein, Nikolaidis, Konstantinos, Plagemann, Thomas, Goebel, Vera, Traaen, Gunn Marit, Øverland, Britt, Aakerøy, Lars, Hunt, Tove-Elizabeth, Loennechen, Jan Pål, Steinshamn, Sigurd Loe, Bendz, Christina Holt, Anfinsen, Ole-Gunnar, Gullestad, Lars, Akre, Harriet
Sleep apnea is a serious and severely under-diagnosed sleep-related respiration disorder characterized by repeated disrupted breathing events during sleep. It is diagnosed via polysomnography which is an expensive test conducted in a sleep lab requir
Externí odkaz:
http://arxiv.org/abs/2101.02595
Autor:
Nikolaidis, Konstantinos, Plagemann, Thomas, Kristiansen, Stein, Goebel, Vera, Kankanhalli, Mohan
Improper or erroneous labelling can pose a hindrance to reliable generalization for supervised learning. This can have negative consequences, especially for critical fields such as healthcare. We propose an effective new approach for learning under e
Externí odkaz:
http://arxiv.org/abs/2009.11128
Autor:
Nikolaidis, Konstantinos, Kristiansen, Stein, Plagemann, Thomas, Goebel, Vera, Liestøl, Knut, Kankanhalli, Mohan, Traaen, Gunn Marit, Øverland, Britt, Akre, Harriet, Aakerøy, Lars, Steinshamn, Sigurd
In this work, we present an approach for unsupervised domain adaptation (DA) with the constraint, that the labeled source data are not directly available, and instead only access to a classifier trained on the source data is provided. Our solution, i
Externí odkaz:
http://arxiv.org/abs/2009.10799
Autor:
Nikolaidis, Konstantinos, Kristiansen, Stein, Plagemann, Thomas, Goebel, Vera, Liestøl, Knut, Kankanhalli, Mohan, Traaen, Gunn Marit, Øverland, Britt, Akre, Harriet, Aakerøy, Lars, Steinshamn, Sigurd
Publikováno v:
Journal of Artificial Intelligence Research 72 (2021): 1163-1214
Good training data is a prerequisite to develop useful ML applications. However, in many domains existing data sets cannot be shared due to privacy regulations (e.g., from medical studies). This work investigates a simple yet unconventional approach
Externí odkaz:
http://arxiv.org/abs/2009.10007
Autor:
Nikolaidis, Konstantinos, Kristiansen, Stein, Goebel, Vera, Plagemann, Thomas, Liestøl, Knut, Kankanhalli, Mohan
Publikováno v:
ECML-PKDD 2019
Supervised machine learning applications in the health domain often face the problem of insufficient training datasets. The quantity of labelled data is small due to privacy concerns and the cost of data acquisition and labelling by a medical expert.
Externí odkaz:
http://arxiv.org/abs/1905.09068
Driven by the goal to enable sleep apnea monitoring and machine learning-based detection at home with small mobile devices, we investigate whether interpretation-based indirect knowledge transfer can be used to create classifiers with acceptable perf
Externí odkaz:
http://arxiv.org/abs/1903.02313
Autor:
Kristiansen, Stein, Nikolaidis, Konstantinos, Plagemann, Thomas, Goebel, Vera, Traaen, Gunn Marit, Øverland, Britt, Akerøy, Lars, Hunt, Tove-Elizabeth, Loennechen, Jan Pål, Steinshamn, Sigurd Loe, Bendz, Christina Holt, Anfinsen, Ole-Gunnar, Gullestad, Lars, Akre, Harriet
Publikováno v:
In Smart Health March 2023 27
Akademický článek
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Autor:
Längle, Gerhard, Raschmann, Svenja, Heinsch, Anna, Großmann, Tamara, Fischer, Lasse, Timm, Jürgen, Bechdolf, Andreas, von Peter, Sebastian, Weinmann, Stefan, Nikolaidis, Konstantinos, Brieger, Peter, Hamann, Johannes, Waldmann, Tamara, Schwarz, Julian, Rout, Sandeep, Herwig, Uwe, Richter, Janina, Hirschmeier, Constance, Baumgardt, Johanna, Holzke, Martin
Publikováno v:
Psychiatrische Praxis; May2024, Vol. 51 Issue 4, p202-208, 7p