Zobrazeno 1 - 10
of 232
pro vyhledávání: '"Rüdiger, Pryss"'
Autor:
Anna Horn, Julia Wendel, Isabella Franke, Armin Bauer, Harald Baumeister, Eileen Bendig, Sara Y. Brucker, Thomas M. Deutsch, Patricia Garatva, Kirsten Haas, Lorenz Heil, Klemens Hügen, Helena Manger, Rüdiger Pryss, Viktoria Rücker, Jessica Salmen, Andrea Szczesny, Carsten Vogel, Markus Wallwiener, Achim Wöckel, Peter U. Heuschmann, the BETTER-CARE Study Group
Publikováno v:
Trials, Vol 25, Iss 1, Pp 1-13 (2024)
Abstract Background The risk of breast cancer patients for long-term side effects of therapy such as neurotoxicity and cardiotoxicity as well as late effects regarding comorbidities varies from individual to individual. Personalised follow-up care co
Externí odkaz:
https://doaj.org/article/fd61e6d7c0334e868bd4b28a3617d320
Publikováno v:
npj Digital Medicine, Vol 7, Iss 1, Pp 1-10 (2024)
Abstract This perspective article explores how process mining can extract clinical insights from mobile health data and complement data-driven techniques like machine learning. Despite technological advances, challenges such as selection bias and the
Externí odkaz:
https://doaj.org/article/44f5b70dee014e148e17be072ab0121b
Autor:
Abdul Rahman Idrees, Felix Beierle, Agnes Mutter, Robin Kraft, Patricia Garatva, Harald Baumeister, Manfred Reichert, Rüdiger Pryss
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-14 (2024)
Abstract The challenge of sustaining user engagement in eHealth interventions is a pressing issue with significant implications for the effectiveness of these digital health tools. This study investigates user engagement in a cognitive-behavioral the
Externí odkaz:
https://doaj.org/article/925629a10c834281a4a5cbda739f3594
Publikováno v:
Child and Adolescent Psychiatry and Mental Health, Vol 18, Iss 1, Pp 1-9 (2024)
Abstract Background Mental health in adolescence is critical in its own right and a predictor of later symptoms of anxiety and depression. To address these mental health challenges, it is crucial to understand the variables linked to anxiety and depr
Externí odkaz:
https://doaj.org/article/a10872b532354436ab8890237e2d6559
Autor:
Johannes Allgaier, Rüdiger Pryss
Publikováno v:
Machine Learning and Knowledge Extraction, Vol 6, Iss 2, Pp 1378-1388 (2024)
This study delves into the multifaceted nature of cross-validation (CV) techniques in machine learning model evaluation and selection, underscoring the challenge of choosing the most appropriate method due to the plethora of available variants. It ai
Externí odkaz:
https://doaj.org/article/c81b3fc14e7c43c2b5180c86d1be0b7d
Autor:
Rüdiger Pryss, Jan vom Brocke, Manfred Reichert, Enrico Rukzio, Winfried Schlee, Barbara Weber
Publikováno v:
Frontiers in Neuroscience, Vol 18 (2024)
Externí odkaz:
https://doaj.org/article/308d838696e84ee8a1bba6476494bb94
Publikováno v:
Frontiers in Neuroscience, Vol 18 (2024)
Externí odkaz:
https://doaj.org/article/aaa6531290c44908a746d0bdaedbe25f
Publikováno v:
Journal of Medical Internet Research, Vol 26, p e45530 (2024)
BackgroundSpecialized studies have shown that smartphone-based social interaction data are predictors of depressive and anxiety symptoms. Moreover, at times during the COVID-19 pandemic, social interaction took place primarily remotely. To appropriat
Externí odkaz:
https://doaj.org/article/f1e6971d511845ac8b8a198bc8bfe9e5
Autor:
Rinat Meerson, Hanna Buchholz, Klaus Kammerer, Manuel Göster, Johannes Schobel, Christoph Ratz, Rüdiger Pryss, Regina Taurines, Marcel Romanos, Matthias Gamer, Julia Geissler
Publikováno v:
Frontiers in Digital Health, Vol 6 (2024)
IntroductionChallenging behaviour (CB) is a common issue among children with autism spectrum disorder or intellectual and developmental disability. Mental health applications are low-threshold cost-effective tools to address the lack of resources for
Externí odkaz:
https://doaj.org/article/6f9fd9216a32486493d8337079c4a098
Autor:
Johannes Allgaier, Rüdiger Pryss
Publikováno v:
Communications Medicine, Vol 4, Iss 1, Pp 1-11 (2024)
Abstract Background Machine learning (ML) models are evaluated in a test set to estimate model performance after deployment. The design of the test set is therefore of importance because if the data distribution after deployment differs too much, the
Externí odkaz:
https://doaj.org/article/ed42e7216cac4a1c8c265b81f44e47ff