August 16, 2021Open Access

Deep learning-based predictive biomarker of pathological complete response to neoadjuvant chemotherapy from histological images in breast cancer

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Resumen

The DL-based pCR-score from histological images is predictive of pCR better than sTILs and subtype, and holds the great potentials for a more accurate stratification of patients for NAC.

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Li et al. (Mon,) studied this question.

synapsesocial.com/papers/69e1117e1810c33ec945915c https://doi.org/https://doi.org/10.1186/s12967-021-03020-z

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

1Computer Vision: A Reference Guide2014 · 178 citations
2Integrative cluster classification to predict pathological complete response to neoadjuvant chemotherapy in early breast cancer.2018 · 8 citations
3Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer2017 · 3,308 citations
4Pathological complete response and long-term clinical benefit in breast cancer: the CTNeoBC pooled analysis2014 · 4,723 citations
5A two-gene epigenetic signature for the prediction of response to neoadjuvant chemotherapy in triple-negative breast cancer patients2019 · 65 citations

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