Automated Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy in Breast Carcinoma Using Deep Learning on Pretreatment Core Needle Biopsy Samples
Our AI-based model accurately predicted pCR to NAC in breast carcinoma using only a limited number of high-cellularity image patches and basic clinical metadata, without requiring expert annotation. This approach may facilitate earlier treatment decisions and improve preoperative outcome prediction.
Authors
- Mingxi Yang
- Seoung Wan Chae (ORCID: https://orcid.org/0000-0003-0406-4469)
- Joon Koo Han (ORCID: https://orcid.org/0000-0001-5916-5545)
- Helen Won (ORCID: https://orcid.org/0000-0001-5237-7529)
- Hyun Soo Kim (ORCID: https://orcid.org/0000-0002-2356-7822)
- Sung‐Im Do (ORCID: https://orcid.org/0000-0001-8442-5054)
Institutions
- Samsung Medical Center (KR)
- Kangbuk Samsung Hospital (KR)
- Sungkyunkwan University (KR)
Publication Details
- Journal
- Anticancer Research
- Published
- 2025-10-28
- DOI
- https://doi.org/10.21873/anticanres.17856
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00