Blockchain-Based Ensemble Deep Learning Model Technique for Breast Cancer Classification

Breast cancer is a condition brought on by the uncontrollable growth and multiplication of aberrant cells in the breast tissue. The misdiagnosis of breast cancer can result in needless or delayed therapies, mental and physical health, increased anxiety and stress, and decreased survival rates for patients. Also, the exchange of healthcare data is difficult to secure due to strict privacy laws, online threats, and the possibility of human error. Blockchain technology can enhance the security and privacy of patient data, give patients greater control over their health data, and facilitate safe data exchange between healthcare providers. In this study, we propose a Blockchain-based Ensemble Deep Learning Model method that can classify Breast Cancer either Malignant or Benign. This method is built on combining different breast cancer classification ANN models and sharing them through blockchain to use their weights to train and optimize the performance of a final model. This model achieved 98% accuracy, and showed a promising in protecting patients from fatal diagnosis mistakes.