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Artificial Intelligence in Health AI in early breast cancer diagnosis: A review

Funding 2000. Available from: https://www.ncbi.nlm.nih.gov/books/
NBK225187 [Last accessed on 2024 Jul 09].
None.
6. Li J, Guan X, Fan Z, et al. Non-invasive biomarkers for early
Conflict of interest detection of breast cancer. Cancers (Basel). 2020;12(10):2767.

The authors declare that they have no competing interests. doi: 10.3390/cancers12102767
7. El-Toukhy SE, El-Daly SM, Kamel MM, Nabih HK. The
Author contributions diagnostic significance of circulating miRNAs and metabolite
profiling in early prediction of breast cancer in Egyptian
Conceptualization: All authors women. J Cancer Res Clin Oncol. 2023;149(8):5437-5451.
Formal analysis: All authors
Investigation: Saadia Humayun doi: 10.1007/s00432-022-04492-2
Methodology: All authors 8. Sood R, Rositch AF, Shakoor D, et al. Ultrasound for breast
Writing – original draft: Saadia Humayun cancer detection globally: A systematic review and meta-
Writing – review & editing: All authors analysis. J Glob Oncol. 2019;5:1-17.
doi: 10.1200/JGO.19.00127
Ethics approval and consent to participate
9. Sharma S, Vicenty-Latorre FG, Elsherif S, Sharma S. Role of
Not applicable. MRI in breast cancer staging: A case-based review. Cureus.
2021;13(12):e20752.
Consent for publication
doi: 10.7759/cureus.20752
Not applicable. 10. Steyerova P, Burgetova A. Current imaging techniques and

Availability of data impact on diagnosis and survival--a narrative review. Ann
Breast Surg. 2022;6:25.
All data analyzed in this review are from published studies doi: 10.21037/abs-21-22
cited in the references.
11. Liew XY, Hameed N, Clos J. A review of computer-aided
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Volume 2 Issue 2 (2025) 114 doi: 10.36922/aih.4197