Breast Cancer Disease Prediction using Convolutional Neural Networks with Ultrasound Image Dataset for Healthcare-IOT Application
Ankit Kumar Dwivedi, Anjulata Yadav, Radhe Shyam Gamad · 2025
Breast cancer stands as one of the leading severe health conditions which affect women globally. The early discovery of breast cancer conditions makes treatment success and recovery potential much higher. Traditional diagnostic tools especially mammography become illusive and difficult to interpret when used in rural areas. This research demonstrates an approach to breast cancer detection through the application of Convolutional Neural Networks (CNNs) on ultrasound pictures. The goal of studying ultrasound pictures involves creating an automatic system which identifies benign or malignant tumors to expedite breast cancer detection. The innovative technology can operate within Healthcare-IoT infrastructure by uniting CNNs with the risk-free ultrasonography method. The proposed methodology can help healthcare providers in restricted regions obtain faster diagnosis decisions that will boost patient healthcare access. The system shows great promise for healthcare applications because its performance is evaluated through accuracy, precision, recall and F1 score measures.