Case Study
Human Data Science and Mental Health
Advanced analytics and human expertise enable suicide risk detection

Applying Human Data Science to mental health is an emerging field of research. Through advanced analytics and human expertise, Human Data Science can enable methodologies that offer improved disease understanding, acute risk assessment and intervention. A crisis intervention app based on machine learning and natural language processing algorithms can detect risk of suicidal thoughts or self-harm based on data from real-time text messages from people in crisis. Data produced from the messages can be fed back into the algorithm to further train the model and shared with other healthcare stakeholders in a privacy protected manner, enabling future research for mental health.

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