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Identifying mental health status using deep neural network trained by visual metrics

Medicine and Health

Identifying mental health status using deep neural network trained by visual metrics

S. B. Shafiei, Z. Lone, et al.

This innovative study, conducted by Somayeh B. Shafiei, Zaeem Lone, Ahmed S. Elsayed, Ahmed A. Hussein, and Khurshid A. Guru, presents an objective method for mental health evaluation through a CNN-LSTM model utilizing visual metrics time-series data. With impressive classification accuracy rates, this research opens the door for at-home mental health monitoring applications.

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