Tongue Based Disease Prediction Using ANN Algorithm Comparing with RNN

The study focuses on accurately predicting tongue-based diseases using advanced deep learning algorithms, specifically comparing the performance of Artificial neural network and Recurrent Neural Networks. To assess the effectiveness of these algorithms, a pretest power analysis was conducted with a power level of 80%, and a sample size of 20 was used for each group. The analysis involved evaluating the performance of ANN and RNN in predicting disease accuracy, with both algorithms being tested on the same dataset. The results showed that both the ANN and RNN algorithms achieved an accuracy score of 10. However, a statistical analysis using two-tailed t-tests revealed a significant difference in precision between the two methods, with a p-value of 0.002 (p < 0.05). This indicates that the ANN outperformed the RNN in terms of prediction precision.