Predictive Diagnosis of Breast Cancer Tissues using Machine Learning Approaches

Le résumé fourni par la source

The second most common cancer and the second most deadly form of cancer among women is breast cancer, with an early detection being a major factor in improving the rates of survival. The last many years have seen a number of most exciting developments in the machine learning (ML) community that have the potential to immediately impact the accuracy and reliability of breast cancer diagnoses. In this paper, we present and apply the new tools these bright minds have developed to the most important problem breast cancer detection and, at the same time, funding a new human resource model for doing so in a timely and cost-effective manner. Our study is concerned not just with the direct issue of improving breast cancer detection but also with the bigger question of how well these new ML tools might work in the overall context of healthcare diagnostics.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.