Experiencing a mental health crisis has a detrimental impact on a patient’s life. A machine learning algorithm trained retrospectively with electronic health records can predict almost 60% of mental health crises 4 weeks in advance. Prospective evaluation of the algorithm in clinical practice reveals its potential to enable preemptive interventions.
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References
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This is a summary of: Garriga, R. et al. Machine learning model to predict mental health crises from electronic health records. Nat. Med. https://doi.org/10.1038//s41591-022-01811-5 (2022).
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Machine learning paves the way toward the prevention of mental health crises. Nat Med 28, 1135–1136 (2022). https://doi.org/10.1038/s41591-022-01820-4
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DOI: https://doi.org/10.1038/s41591-022-01820-4
