Article Versions Notes

Lio G, Ghazzai M, Haesebaert F, Dubreucq J, Verdoux H, Quiles C, Jaafari N, Chéreau-Boudet I, Legros-Lafarge E, Guillard-Bouhet N, et al. Actionable Predictive Factors of Homelessness in a Psychiatric Population: Results from the REHABase Cohort Using a Machine Learning Approach. International Journal of Environmental Research and Public Health. 2022; 19(19):12268. https://doi.org/10.3390/ijerph191912268

Lio, Guillaume, Malek Ghazzai, Frédéric Haesebaert, Julien Dubreucq, Hélène Verdoux, Clélia Quiles, Nemat Jaafari, Isabelle Chéreau-Boudet, Emilie Legros-Lafarge, Nathalie Guillard-Bouhet, and et al. 2022. "Actionable Predictive Factors of Homelessness in a Psychiatric Population: Results from the REHABase Cohort Using a Machine Learning Approach" International Journal of Environmental Research and Public Health 19, no. 19: 12268. https://doi.org/10.3390/ijerph191912268

Lio, G., Ghazzai, M., Haesebaert, F., Dubreucq, J., Verdoux, H., Quiles, C., Jaafari, N., Chéreau-Boudet, I., Legros-Lafarge, E., Guillard-Bouhet, N., Massoubre, C., Gouache, B., Plasse, J., Barbalat, G., Franck, N., & Demily, C. (2022). Actionable Predictive Factors of Homelessness in a Psychiatric Population: Results from the REHABase Cohort Using a Machine Learning Approach. International Journal of Environmental Research and Public Health, 19(19), 12268. https://doi.org/10.3390/ijerph191912268