Knowledge-guided Multimodal Learning for Interpretable Prediction of Pathological Complete Response and Survival in Breast Cancer
AI combining pathology images with clinical data may help predict which breast cancer patients will respond fully to chemotherapy before treatment begins.
PURPOSE: Pretreatment estimation of pathological complete response (pCR) to neoadjuvant chemotherapy may support risk stratification and future response-adapted clinical studies in breast cancer. CONCLUSIONS: These findings suggest that pathology-informed multimodal learning may provide a candidate framework for pretreatment risk stratification.
What the study was
- Study design
- Observational/Cohort Study
- Population
- PURPOSE: Pretreatment estimation of pathological complete response (pCR) to neoadjuvant chemotherapy
- Sample size
- 1486
- Category
- Diagnostics
- Maturity
- Validated
- Journal
- Laboratory investigation; a journal of technical methods and pathology
Why it surfaced
moderate relevance to watchlist
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