Objective: To predict the classification type as benign or malignant

Input: Segmented image features (|R|)

Output: Classification predictions (yi )

1: Feature extraction using Improved GLCM (I-GLCM)

2: Compute mean (μ) using Eq. (13)

3: Compute standard deviation (τ) using Eq. (14)

4: Compute contrast using Eq. (15)

5: Compute dissimilarity using Eq. (16)

6: Initialize U-Net architecture

7: for each time step t do

8: Calculate update gate zt using Eq. (18)

9: Calculate reset gate rt using Eq. (19)

10: Calculate the candidate’s hidden state $k_t^{\sim }$ using Eq. (20)

11: Update hidden state kt using Eq. (21)

12: Generate classification predictions:

13: for each output unit i do

14: Compute predictions yi using ReLU activation on the final hidden state kt

15: end for

16: return Classification predictions (yi )