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Accurate breast cancer (BC) diagnosis is a difficult task that is critical for the proper treatment of BC in IoMT (Internet of Medical Things) healthcare systems. This paper proposes a convolutional neural network (CNN)-based diagnosis method for detecting early-stage breast cancer. In developing the proposed method, we incorporated the CNN model for the invasive ductal carcinoma (IDC) classification using breast histology image data. We have incorporated transfer learning (TL) and data augmentation (DA) mechanisms to improve the CNN model's predictive outcomes. For the fine-tuning process, the CNN model was trained with breast histology image data. Furthermore, the held-out cross-validation method for best model selection and hyper-parameter tuning was incorporated. In addition, various performance evaluation metrics for model performance assessment were computed. The experimental results confirmed that the proposed model outperformed the baseline models across all evaluation metrics, achieving 99.04% accuracy. We recommend the proposed method for early recognition of BC in IoMT healthcare systems due to its high performance.

Trace elements are essentially required for various physiological and metabolic functions, and any disturbance in the trace elements homeostasis may result in the development of chronic diseases including breast cancer. Breast cancer is the most prevalent cancer type reported in women equally affecting both the high-income and low-income countries. This review therefore aimed to evaluate the impact of dietary trace element intake in relation to the incidence of breast cancer. We focused on five trace elements, thus emphasizing dietary selenium, zinc, iron, copper, and cadmium intake and risk of breast cancer. A systematic approach was applied to perform this review through entering a search term in PubMed and Scopus databases. A total of 24 articles were included after meeting the inclusion and exclusion criteria. Most of the studies regarding dietary iron intake showed a detrimental effect of increased dietary heme iron on breast cancer incidence risk. In addition, there is a limited evidence of high dietary intake of selenium and zinc to reduce the risk of breast cancer. Also, a few studies showed a relationship between high cadmium consumption and risk of breast cancer. More studies related to cadmium and copper exposure are needed to confirm this relationship. As a result, the findings of this review suggested that high dietary heme iron is a potential risk factor for breast cancer., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)