Student Mental Health AI Reached 95% Accuracy in Kaggle Data
A 2026 PLOS One machine-learning study reported 95.0% accuracy for a hybrid FT-Transformer plus long short-term memory (LSTM) model predicting student mental-health risk. The technical result is strong inside the dataset, but the clinical claim is still limited because the labels came from repository data rather than prospective clinical diagnosis.1 Research Highlights 95.0% accuracy was …
