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91% Accurate Early Risk Detection using MEandMine Deep Learning and In-Game Behavioral Signals.
Our data scientists and researchers ground MEandMine’s innovation in behavioral data and neuroscience.
The team uses gamified and adaptive self-regulation activities to address the root causes of behavior incidents, chronic absenteeism and the widening gap between students in emotional distress and available counselors.
We use Deep Learning to analyze large-scale behavioral and well-being data to train our Preventive AI for detection.
By enabling earlier insight and intervention, MEandMine helps student regulate emotions while detecting early mental health risk, reducing the critical gap of 11 years.
Neuro-Regulation Model
After 10–15 minutes of practice, students show measurable gains in self-regulation, nearly doubling learning readiness.
AI-Flagging Model
Detect early risk patterns of anxiety, depression, ADHD symptoms, and aggression.
Risk Detection Model
Anomaly (Abnormal) Cutoff: Reconstruction Error > mean + 3.2 std


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