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Titlebook: GeNeDis 2020; Computational Biolog Panayiotis Vlamos Conference proceedings 2021 The Editor(s) (if applicable) and The Author(s), under exc

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31#
發(fā)表于 2025-3-26 21:05:17 | 只看該作者
Bioinformatics Analyses of Spatial Peripheral Circadian Clock-Mediated Gene Expression of Glucocorte Bayes classification, and polynomial regression analyses. We determined expression patterns of Clock-related genes, unraveled the dynamics of spatial data, and defined the temporal function of Clock-mediated GR-regulated genes. Gene expressions manifested nonlinear dynamics, possibly because we ob
32#
發(fā)表于 2025-3-27 02:41:07 | 只看該作者
Mobile Application for Monitoring and Preventing Cognitive Decline Through Lifestyle Intervention,he individual’s progress. The developed application is also capable of reassessing users’ risk to track their progress, while also providing these services in an intuitive and user-friendly manner, which could enable the future development of more accurate models through the collected data.
33#
發(fā)表于 2025-3-27 06:29:29 | 只看該作者
34#
發(fā)表于 2025-3-27 10:39:43 | 只看該作者
Validation of the Greek Version of Social Media Disorder Scale,with exploratory factor analysis. Exploratory factor analysis resulted in a single factor model, which explained almost half of the total variance. The Greek version of SMDS is a psychometrically sound and valid instrument, which researchers and practitioners can use to assess social media addiction
35#
發(fā)表于 2025-3-27 17:16:31 | 只看該作者
36#
發(fā)表于 2025-3-27 20:41:52 | 只看該作者
37#
發(fā)表于 2025-3-27 22:16:25 | 只看該作者
https://doi.org/10.1007/978-3-642-57712-3s and depending on the type of datasets. Hierarchal clustering algorithm was used to detect gene patterns in our candidate datasets, since microarray data are considered big and complex. Systematic sampling technique was used to reduce the complexity of microarray datasets and to enhance the cluster
38#
發(fā)表于 2025-3-28 03:52:39 | 只看該作者
Invarianz des mathematischen Selbstkonzeptsression, Naive Bayes, Support Vector Machine and Gradient Boosting Classification, all of which are used for the classification of new patients based on a dataset that includes information from previous breast cancer incidents. The results depict that the optimal algorithm based on the current metho
39#
發(fā)表于 2025-3-28 06:22:31 | 只看該作者
Die Resultate der Untersuchung,thms to extract patterns of personality, as modeled by the Big Five personality traits. The utilized algorithms turn out to be effective at predicting drug use for most of the 17 drugs that are considered, even in cases of high-class imbalance.
40#
發(fā)表于 2025-3-28 12:21:48 | 只看該作者
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