Multi-Centre Deep Learning Study Targets Digital Breast Tomosynthesis Accuracy — 5,000 Patient Validation for AI-Enhanced Breast Cancer Diagnosis
247 Health News Editorial
·8 June 2026
·4 min read
·clinical-trialsA groundbreaking 5,000-patient study aims to validate deep learning technology for comprehensive digital breast tomosynthesis interpretation, targeting improved accuracy in breast cancer diagnosis and treatment planning. The multi-centre trial addresses critical gaps in AI-assisted breast imaging across the entire care pathway.
Originally reported by ClinicalTrials.gov
References
- 1.Yunnan Cancer Hospital. (2024). Research on the Whole-Process Intelligent Diagnosis and Treatment of Digital Breast Tomosynthesis Based on Deep Learning: Multicenter Retrospective and Prospective Validation. ClinicalTrials.gov. NCT07605195. https://clinicaltrials.gov/study/NCT07605195
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- 5.Hickman, S. E., Baxter, S. L., Boone, J. M., Hsieh, M. K., Keaveny, E., Lourenco, A. P., Sickles, E. A., Burnside, E. S., & Hoyt, A. C. (2022). Artificial intelligence for breast cancer screening: opportunity or hype? Journal of the American College of Radiology, 19(10), 1130-1138. https://doi.org/10.1016/j.jacr.2021.12.017
- 6.Sung, H., Ferlay, J., Siegel, R. L., Laversanne, M., Soerjomataram, I., Jemal, A., & Bray, F. (2021). Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA: A Cancer Journal for Clinicians, 71(3), 209-249. https://doi.org/10.3322/caac.21660
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247 Health News Editorial
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