Abstract

Prasurjya Saikia76080*, Durgaprasad Kemisetti76081, Ananga Mohan Das76082, Charlisar Teron76083 and Diptimonta Neog76084

Improving patient outcomes depends critically on the early identification of breast cancer. Artificial Intelligence (AI) has the potential to completely transform Breast Cancer (BC) screening by enabling detection up to five years before a clinical diagnosis. This paper examines this possibility and explores the most recent developments in AI algorithms, particularly in relation to medical imaging, such as mammography.

We investigate how AI can identify precancerous alterations that are often invisible to the human eye by analyzing minute patterns in breast tissue. Additionally, we discuss the challenges and opportunities associated with developing and evaluating AI models for early detection, including issues of model interpretability, data quality and ethical considerations.

The ultimate goal of this analysis is to demonstrate how AI can significantly reduce BC mortality by facilitating much earlier detection.