Tumor microenvironment and the role of artificial intelligence in breast cancer detection and prognosis
Cet article analyse le rôle de l'intelligence artificielle dans la détection d'un cancer du sein, l'établissement de son pronostic et l'exploitation des données concernant le microenvironnement tumoral
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.Despite the significant potential AI holds, there is still much debate surrounding the appropriate and ethical curation of medical data from Picture Archiving and Communication Systems (PACS). Artificial Intelligence (AI) output's clinical significance holds its outcome based on its human predecessor's data training sets. Integration between biomarkers, risk factors, and imaging data will allow the best predictor models for patient-based outcomes.
The American Journal of Pathology , article en libre accès, 2020