Jakarta, INTI – Amid the rising number of breast cancer cases reported each year, researchers have introduced a breakthrough that may help identify risks much earlier. Delayed diagnoses often caused by the limited accuracy of mammography remain a major challenge in prevention efforts. To address this need, a new artificial intelligence (AI) model was presented in a recent study released in early December 2025, offering a predictive solution through mammogram image analysis. This technology is believed to help women understand their breast cancer risk up to five years in advance, even when their mammogram results appear normal.
AI Bridges the Gap in Early Breast Cancer Detection
Each year, more than 2.3 million breast cancer cases are detected worldwide, and over 670,000 women lose their lives to the disease. According to Christiane Kuhl, Director of the Department of Diagnostic and Interventional Radiology at RWTH Aachen University Hospital, mammography still often fails to detect fast-growing and aggressive tumors the most lethal type for many women.
The new AI model addresses these limitations. The algorithm can classify a person’s risk level solely through mammogram analysis, without requiring genetic data, family history, or lifestyle information.
Four Times More Accurate in Identifying Risk
In the study, women categorized by the AI as high-risk were found to be four times more likely to develop breast cancer compared to those classified as low-risk. The AI can predict risks up to five years ahead, even when mammogram results show no abnormalities.
Kuhl emphasized that this technology enables screening to become far more precise and personalized. Factors such as breast tissue density, texture, and tissue composition are deeply analyzed by the system to determine actual risk levels.
The Need for More Personalized Screening
In many countries, including Germany, mammogram screenings are offered every two years for women aged 50 to 75. However, this uniform approach is increasingly considered outdated. Every woman has different risk levels, especially those with dense breast tissue making mammography less accurate in detecting cancer.
In the United States, women are even required to be informed about their breast density and the risk of “masking” when breast cancer is not visible through mammography.
MRI Considered More Reliable for Early Detection
With the growing need for early detection among high-risk groups, MRI technology is considered more effective than mammography or ultrasound. However, MRI examinations are significantly more expensive. For this reason, the Clairity Consortium an international research association consisting of 46 institutions developed an AI model called Clairity Breast.
This model was trained using more than 420,000 mammograms from Europe and the Americas, making it one of the most comprehensive systems for independently and accurately detecting breast cancer risk.
A Two-Step Approach: Mammography + AI Analysis
Kuhl believes screening should not rely solely on age. Although younger women generally have lower risks, they are more likely to develop aggressive tumors and have denser breast tissue, making early detection through mammography more difficult.
She proposes a two-step approach:
- Initial mammography,
- Followed by AI-based risk analysis.
If the algorithm indicates a very high risk level, the woman should be offered an MRI for deeper detection without needing an additional mammogram.
Conclusion
The latest AI technology offers a major opportunity to improve early breast cancer detection, which has long depended on methods that are not fully accurate. With its ability to analyze mammograms in detail and predict risks up to five years ahead, this model has the potential to save more lives through a screening approach that is more personalized, precise, and efficient. This innovation marks an important step toward a future of cancer detection that is more adaptive and effective.
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