AI News
Breakthrough as AI Predicts Breast Cancer Risk Years Before Diagnosis – Study Finds

- AI can predict breast cancer risk up to six years before diagnosis, according to a study analyzing over 116,000 mammograms.
- The algorithm identified which breast was at risk, with cancerous breasts scoring nearly twice as high as the other.
- Researchers say AI could improve early detection programs, reducing healthcare costs and targeting at-risk women more effectively.
Artificial intelligence can identify women at an elevated risk of developing breast cancer years before diagnosis, the Norwegian Institute of Public Health (FHI) announced Tuesday.
EKO HOT BLOG reports that a team of researchers from FHI, the University of California, and the University of Washington analyzed mammograms from 116,495 women who participated in a Norwegian detection program between 2004 and 2018.
Using a commercially available AI program, they found that the algorithm could predict which women were more likely to develop breast cancer—up to six years before a formal diagnosis.
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Of the women studied, 1,607 were later diagnosed with breast cancer. The AI system not only identified those at higher risk but also pinpointed which breast was more likely to develop the disease.
“We noted that the breast which developed cancer had an AI score about twice as high as the other breast,” said Solveig Hofvind, head of the detection program and the AI project.
The findings suggest that existing AI tools could help create more personalized breast cancer detection programs, potentially improving early diagnosis and reducing healthcare costs, FHI stated.
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Breast cancer remains the most common cancer among women worldwide, with 670,000 deaths recorded in 2022, according to the World Health Organization.
The study was published in the Journal of the American Medical Association Network. Meanwhile, Norway’s detection program has launched another AI study involving 140,000 women to assess whether AI could match or surpass radiologists in diagnosing breast cancer.
(AFP)
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