Deep learning is frequently used in medical applications such as detection of the type of cancerous cells. Breast cancer is a type of cancer that occurs mostly in females and is the leading cause of women’s deaths.
The cancerous cells are classified as Normal or Mild or Severe. These deaths can be reduced by early detection of the cancerous cells. Cancerous cells are detected by performing various tests like MRI, mammogram, ultrasound and biopsy. The diagnosis of breast cancer histology images with haematoxylin and eosin stained is non-trivial, labour-intensive and often leads to a disagreement between pathologists.
With the recent advances in deep learning, convolutional neural networks (CNNs) and VGG-19 have been successfully used for histology images analysis. Finally, the system can estimate the accuracy and error rate effectively.

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