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- research-articleNovember 2024
Machine learning for anxiety and depression profiling and risk assessment in the aftermath of an emergency
- Guillermo Villanueva Benito,
- Ximena Goldberg,
- Nicolai Brachowicz,
- Gemma Castaño-Vinyals,
- Natalia Blay,
- Ana Espinosa,
- Flavia Davidhi,
- Diego Torres,
- Manolis Kogevinas,
- Rafael de Cid,
- Paula Petrone
Artificial Intelligence in Medicine (AIIM), Volume 157, Issue Chttps://doi.org/10.1016/j.artmed.2024.102991Abstract Background & objectivesMental health disorders pose an increasing public health challenge worsened by the COVID-19 pandemic. The pandemic highlighted gaps in preparedness, emphasizing the need for early identification of at-risk groups and ...
Highlights- The COVID-19 pandemic and lockdown worsened mental health, revealing a lack of preparedness to address this growing crisis.
- Interpretable machine learning predicts depression, anxiety, and stress, highlighting factors like poor health ...