A critical gap of knowledge has been noted in breast cancer detection, prognosis, and evaluation between tumor microenvironment and associated neoplasm. Artificial intelligence has multiple subsets or methods for data extraction and evaluation, including artificial neural networking, which allows computational foundations, similar to neurons, to make connections and new neural pathways during data set training. Deep machine learning and artificial intelligence hold great potential to accurately assess Tumour Micro Environment (TME) models employing vast data management techniques.