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English Information

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Authors
# Name
1 Cristiane Nobre(nobre@pucminas.b)
2 Luis Enrique Zarate(zarate@pucminas.br)
3 Marco Paulo Soares(marcopaulo@pucminas.br)
4 Carlos Maia(carlosdiasmaia@gmail.com)

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Reference
# Reference
1 Albert, P. R. Why is depression more prevalent in women? Journal of psychiatry & neuroscience: JPN 40 (4): 219, 2015.
2 Alpaydin, E. Introduction to Machine Learning. Adaptive Computation and Machine Learning. MIT Press, Cambridge, MA, 2014.
3 Blasco, B., García-Jiménez, J., Bodoano, I., and Gutiérrez-Rojas, L. Obesity and depression: Its prevalence and influence as a prognostic factor: A systematic review. Psychiatry investigation vol. 17, 08, 2020.
4 Instituto Brasileiro de Geografia e Estatística. Pesuisa Nacional de Saúde. https://www.ibge.gov.br/ estatisticas/sociais/saude/9160-pesquisa-nacional-de-saude.html?edicao=29270.
5 Kim, H., Yoo, J., Han, K., Fava, M., Mischoulon, D., Park, M. J., and Jeon, H. J. Associations between smoking, alcohol consumption, physical activity and depression in middle-aged premenopausal and postmenopausal women. Frontiers in Psychiatry vol. 12, pp. 2437, 2021.
6 Lal, G. R., Chen, X., and Mithal, V. Te2rules: Extracting rule lists from tree ensembles. arXiv preprint ar- Xiv:2206.14359 , 2022.
7 Lane, M. M., Gamage, E., O’Neil, A., Jacka, F., Marx, W., Dissanayaka, T., Ashtree, D., Travica, N., Gauci, S., and Lotfalian, M. Ultra-processed food consumption and mental health: A systematic review and meta-analysis of observational studies. Nutrients vol. 14, pp. 2568, 06, 2022.
8 Ljungberg, T., Bondza, E., and Lethin, C. Evidence of the importance of dietary habits regarding depressive symptoms and depression. International Journal of Environmental Research and Public Health vol. 17, pp. 1616, 03, 2020
9 McHugh, R. Alcohol use disorder and depressive disorders. Alcohol Research: Current Reviews vol. 40, 10, 2019.
10 Na, K.-S., Cho, S.-E., Geem, Z. W., and Kim, Y.-K. Predicting future onset of depression among community dwelling adults in the republic of korea using a machine learning algorithm. Neuroscience Letters vol. 721, pp. 134804, 01, 2020.
11 Noh, J.-W., Kwon, Y. D., Park, J., Oh, I.-H., and Kim, J. Relationship between physical disability and depression by gender: a panel regression model. PloS one 11 (11): e0166238, 2016.
12 Richter, T., Fishbain, B., Markus, A., Richter-Levin, G., and Okon-Singer, H. Using machine learning-based analysis for behavioral differentiation between anxiety and depression. Scientific Reports vol. 10, 10, 2020.
13 Schmidt-Hieber, J. The kolmogorov–arnold representation theorem revisited. Neural Networks vol. 137, pp. 119–126, 2021.
14 Schonfeld, I. and Bianchi, R. From burnout to occupational depression: Recent developments in research on job-related distress and occupational health. Frontiers in Public Health vol. 9, pp. 1–6, 12, 2021.
15 Sharma, A. and Verbeke, W. J. M. I. Improving diagnosis of depression with xgboost machine learning model and a large biomarkers dutch dataset (n = 11,081). Frontiers in Big Data vol. 3, 2020
16 Woody, C., Ferrari, A., Siskind, D., Whiteford, H., and Harris, M. A systematic review and meta-regression of the prevalence and incidence of perinatal depression. Journal of Affective Disorders vol. 219, pp. 86–92, 2017.