BREAST CANCER DIAGNOSING WITH ARTIFICIAL INTELLIGENCE: CURRENT RESEARCH AND SCIENTIFIC NEWS

Abstract

Breast cancer remains the most common malignancy in women worldwide,
prompting intense interest in artificial intelligence (AI) to enhance diagnostic accuracy and
efficiency. This article reviews both established clinical AI tools and cutting-edge research
developments for breast cancer diagnosis, with a focus on the United States (US), United Kingdom
(UK), and Central Asia (Uzbekistan and Tajikistan). We outline current AI-assisted diagnostic
applications in imaging—particularly mammography—that are in clinical use, including
FDA-cleared decision-support systems, and discuss their variable adoption in healthcare practice.
Recent advances from 2022–2025 are highlighted, such as deep-learning models that match or
surpass radiologist performance in detecting breast malignancies on imaging, AI-driven
risk-prediction models, and digital-pathology algorithms for tumor grading and metastasis
detection. We also examine regional initiatives: large prospective trials in the UK integrating AI
into national screening, U.S. deployments and regulatory approvals, and efforts to introduce AI
diagnostics in Uzbekistan’s healthcare system amid resource constraints. The role of big data is
underscored, as massive annotated datasets and multi-center collaborations have enabled these AI
innovations. Challenges—including data quality, bias, integration into clinical workflows, and the
need for local capacity in Central Asia—are discussed. Overall, AI-driven tools are poised to
augment breast-cancer screening and diagnosis, improving early detection especially in settings
with limited specialists, while ongoing research and trials continue to refine their safety and
effectiveness.