Internet of Things Enabled Deep Convolutional Neural Network Model for Breast Cancer Classification

Healthcare has been a major concern in the research field for the last few decades. Improper management of health conditions may increase the severity of human health. A sensor-equipped Internet of Things (IoT)-based devices advance patient healthcare services. Breast cancer is one of the driving reasons for death among women throughout the world. Detection of cancerous cells and classifying the type of these cells is the major concern to recommend the abnormal region in the breast. This recommendation is required to treat the patient in a better way. Various artificial intelligence-based models including machine learning and deep learning mechanisms are widely applied in the field of classification. This chapter proposed an IoT-enabled patient healthcare model with deep convolutional neural networks (CNNs) recommender system to treat breast cancer. The results were analyzed in terms of computation time, precision, recall, F1-score, and accuracy score with the support of mammogram datasets collected from the UCI repository. The performance of developed deep CNN model outperformed compared to pre-trained CNN-based models VGG16, VGG19, and ResNet-50 for breast cancer classification.