Zobrazeno 1 - 10
of 34
pro vyhledávání: '"Milena Čukić"'
Publikováno v:
JMIR Mental Health, Vol 10, p e40342 (2023)
BackgroundDisturbed heart dynamics in depression seriously increases mortality risk. Heart rate variability (HRV) is a rich source of information for studying this dynamics. This paper is a meta-analytic review with methodological commentary of the a
Externí odkaz:
https://doaj.org/article/6e37e23ab0c840e1a814472640bf68e4
Autor:
Milena Čukić, Victoria López
Publikováno v:
Frontiers in Psychiatry, Vol 13 (2022)
Externí odkaz:
https://doaj.org/article/eb09859e0b39417ab82218adeabd9ba8
Publikováno v:
Frontiers in Physiology, Vol 12 (2022)
Bipolar depression is treated wrongly as unipolar depression, on average, for 8 years. It is shown that this mismedication affects the occurrence of a manic episode and aggravates the overall condition of patients with bipolar depression. Significant
Externí odkaz:
https://doaj.org/article/3cf725bf0bb648288456ea2103a73611
Autor:
Milena Čukić
Publikováno v:
Frontiers in Psychology, Vol 10 (2020)
Externí odkaz:
https://doaj.org/article/b1d38e3ad37b4a46a35f9567f59d6264
Publikováno v:
Mathematics, Vol 9, Iss 11, p 1174 (2021)
There is strong clinical evidence from the current literature that certain psychological and physiological indicators are closely related to mood changes. However, patients with mental illnesses who present similar behavior may be diagnosed different
Externí odkaz:
https://doaj.org/article/eee230c349f641bf8e8bba4a4920ec98
The aim of this work is to give the readers a review (perspective) of prior work on this kind of complexity-based detection from resting-state EEG and present our preliminary cross-section analysis results on how EEG complexity of supposedly healthy
Externí odkaz:
http://arxiv.org/abs/2311.09147
Autor:
Bahrami, Flora, Rossi, René Michel, De Nys, Katelijne, Joerger, Markus, Radenkovic, Milena Cukic, Defraeye, Thijs
Publikováno v:
In European Journal of Pharmaceutical Sciences 1 April 2024 195
After performing comparison of the performance of seven different machine learning models on detection depression tasks to show that the choice of features is essential, we compare our methods and results with the published work of other researchers.
Externí odkaz:
http://arxiv.org/abs/2006.06418
In this paper, we aimed at reviewing present literature on employing nonlinear analysis in combination with machine learning methods, in depression detection or prediction task. We are focusing on an affordable data-driven approach, applicable for ev
Externí odkaz:
http://arxiv.org/abs/1909.03115