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A prospective study of the randomized forest approach to predict the effectiveness of art healing in the treatment of depression

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07. Nov. 2024

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Rigatti, S. J. (2017). Random forest. Journal of Insurance Medicine, 47(1), 31-39. Search in Google Scholar

Speiser, J. L., Miller, M. E., Tooze, J., & Ip, E. (2019). A comparison of random forest variable selection methods for classification prediction modeling. Expert systems with applications, 134, 93-101. Search in Google Scholar

Parmar, A., Katariya, R., & Patel, V. (2019). A review on random forest: An ensemble classifier. In International conference on intelligent data communication technologies and internet of things (ICICI) 2018 (pp. 758-763). Springer International Publishing. Search in Google Scholar

Probst, P., Wright, M. N., & Boulesteix, A. L. (2019). Hyperparameters and tuning strategies for random forest. Wiley Interdisciplinary Reviews: data mining and knowledge discovery, 9(3), e1301. Search in Google Scholar

Paul, A., Mukherjee, D. P., Das, P., Gangopadhyay, A., Chintha, A. R., & Kundu, S. (2018). Improved random forest for classification. IEEE Transactions on Image Processing, 27(8), 4012-4024. Search in Google Scholar

Tang, F., & Ishwaran, H. (2017). Random forest missing data algorithms. Statistical Analysis and Data Mining: The ASA Data Science Journal, 10(6), 363-377. Search in Google Scholar

Resende, P. A. A., & Drummond, A. C. (2018). A survey of random forest based methods for intrusion detection systems. ACM Computing Surveys (CSUR), 51(3), 1-36. Search in Google Scholar

Bosman, J. T., Bood, Z. M., Scherer-Rath, M., Dörr, H., Christophe, N., Sprangers, M. A., & van Laarhoven, H. W. (2021). The effects of art therapy on anxiety, depression, and quality of life in adults with cancer: a systematic literature review. Supportive Care in Cancer, 29, 2289-2298. Search in Google Scholar

Ciasca, E. C., Ferreira, R. C., Santana, C. L., Forlenza, O. V., Dos Santos, G. D., Brum, P. S., & Nunes, P. V. (2018). Art therapy as an adjuvant treatment for depression in elderly women: a randomized controlled trial. Brazilian Journal of Psychiatry, 40, 256-263. Search in Google Scholar

Tang, Y., Fu, F., Gao, H., Shen, L., Chi, I., & Bai, Z. (2019). Art therapy for anxiety, depression, and fatigue in females with breast cancer: A systematic review. Journal of psychosocial oncology, 37(1), 79-95. Search in Google Scholar

Newland, P., & Bettencourt, B. A. (2020). Effectiveness of mindfulness-based art therapy for symptoms of anxiety, depression, and fatigue: A systematic review and meta-analysis. Complementary Therapies in Clinical Practice, 41, 101246. Search in Google Scholar

Hu, J., Zhang, J., Hu, L., Yu, H., & Xu, J. (2021). Art therapy: a complementary treatment for mental disorders. Frontiers in psychology, 12, 686005. Search in Google Scholar

Rowe, C., Watson-Ormond, R., English, L., Rubesin, H., Marshall, A., Linton, K., ... & Eng, E. (2017). Evaluating art therapy to heal the effects of trauma among refugee youth: The Burma art therapy program evaluation. Health promotion practice, 18(1), 26-33. Search in Google Scholar

Zhigang Sun,Weige Tao,Mengmeng Gao,Min Zhang,Shoulai Song & Guotao Wang.(2024).Broiler health monitoring technology based on sound features and random forest.Engineering Applications of Artificial Intelligence108849-108849. Search in Google Scholar

Sumathi Pawar,Manjula Gururaj Rao & Karuna Pandith.(2023).Text document categorisation using random forest and C4.5 decision tree classifier.International Journal of Computational Systems Engineering(2-4),211-220. Search in Google Scholar

MohammadHossein Reshadi,Wen Li,Wenjie Xu,Precious Omashor,Albert Dinh,Scott Dick... & Michael Lipsett.(2024).Deep-Shallow Metaclassifier with Synthetic Minority Oversampling for Anomaly Detection in a Time Series.Algorithms(3),114-. Search in Google Scholar

Oyebayo Ridwan Olaniran,Ali Rashash R. Alzahrani & Mohammed R. Alzahrani.(2024).Eigenvalue Distributions in Random Confusion Matrices: Applications to Machine Learning Evaluation. Mathematics(10), Search in Google Scholar

Yougui Wu.(2024).Optimal two-phase sampling for comparing correlated areas under the ROC curves of two screening tests in the presence of verification bias..Journal of biopharmaceutical statistics11-17. Search in Google Scholar

Sprache:
Englisch
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1 Hefte pro Jahr
Fachgebiete der Zeitschrift:
Biologie, Biologie, andere, Mathematik, Angewandte Mathematik, Mathematik, Allgemeines, Physik, Physik, andere