Deep LSTM Model for Diabetes Prediction with Class Balancing by SMOTE

Diabetes is an acute disease that happens when the pancreas cannot produce enough insulin. It can be fatal if undiagnosed and untreated. If diabetes revealed early enough, it possible, with adequate treatment, to live a healthy life. Recently, researchers have applied artificial intelligence techniques forecasting of diabetes. As result, new SMOTE-based deep LSTM system was developed detect early. This strategy handles class imbalance in dataset, its prediction accuracy measured. article details investigations CNN, CNN-LSTM, ConvLSTM, 1D-convolutional neural network (DCNN) proposed method for prediction. Furthermore, suggested model analyzed towards machine-learning, deep-learning approaches. The model’s measured against dataset achieved highest 99.64%. These results suggest that, based on classification accuracy, this outperforms other methods. recommendation use classifier diabetic patients’ clinical analysis.