As a primary tool, mammography has several limitations, including the high number of false-positive cases and uncertainty in interpretation. Early interventions and effective treatment can make the difference between cure and disease progression. Present methods heavily rely on human interpretation, which can be subjective and time-consuming. The integration of AI into the diagnostic process has the potential to improve sensitivity and reduce false-negative rates from its ability to find and correlate features in images at unprecedented levels. Objectives of the project are: Development of an effective AI-based system for the Analysis of Mammographic Images Reducing False Positives and Uncertainty in Interpretation Integration of Additional Information for Improved Accuracy Reducing Healthcare Costs for Low- and Middle-Income Countries