Sequential autoencoders for feature engineering and pretraining in major depressive disorder risk prediction.

LSTM models with pretrained weights from autoencoders were able to outperform the benchmark and a pretrained Attention model. Future researchers developing risk models in MDD may benefit from the use of LSTM autoencoder pretrained weights.