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Impact of AI on Breast Cancer Detection Rates in Mammography by Radiologists of Varying Experience Levels in Singapore: Preliminary Comparative Study
1
Zitationen
24
Autoren
2025
Jahr
Abstract
This is the first study in Asia to evaluate AI assistance in mammography interpretation by radiologists of varying experience. AI significantly improved diagnostic performance and efficiency among residents, helping to narrow the experience-performance gap without compromising specificity. These findings suggest a role for AI in enhancing diagnostic consistency, improving workflow, and supporting training. Integration into clinical and educational settings may offer scalable benefits, though careful attention to threshold calibration, feedback loops, and real-world validation remains essential. Further studies in routine screening settings are needed to confirm generalizability and cost-effectiveness.
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Autoren
- Serene Si Ning Goh
- Hao Du
- Loon Ying Tan
- E. Seah
- Wai Keat Lau
- Alvin Hong Zhi Ng
- Desmond Shi Wei Lim
- Han Yang Ong
- Samuel Lau
- Yi Liang Tan
- M.J. Khaw
- Chee Woei Yap
- Kei Yiu Douglas Hui
- Wei Chuan Tan
- Haziz Siti Rozana Binti Abdul
- Vanessa Meihui Khoo
- Shuliang Ge
- Felicity Jane Pool
- Yun Song Choo
- Yi Wang
- Pooja Jagmohan
- Patinharayil Gopinathan
- Mikael Hartman
- Mengling Feng