What question did this study set out to answer?

The study aims to determine if pre-treatment clinical and MRI data can predict neoadjuvant chemotherapy response in HER2-positive breast cancer.

July 30, 2026DiagnosticsOpen Access

A Practical Machine Learning Model for Predicting Neoadjuvant Response in HER2-Positive Breast Cancer

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Authors

MAMaría AzmatUniversidade de Santiago de Compostela LGLucía Graña-LópezHospital Universitario Lucus Augusti MFManuel Fernández-DelgadoUniversidade de Santiago de Compostela

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Implication

Randomized trial evaluates predictive performance of machine learning using clinical data in HER2-positive breast cancer, indicating strong implications for treatment planning.

Key Points

The study aims to determine if pre-treatment clinical and MRI data can predict neoadjuvant chemotherapy response in HER2-positive breast cancer.
Retrospective analysis of 112 HER2-positive breast cancer patients treated with neoadjuvant chemotherapy.
Fourteen pre-treatment variables were evaluated, including hormone receptor status and MRI characteristics.
Seventy machine learning classifiers were compared using a fully nested leave-one-out cross-validation framework.
A support vector machine achieved the highest accuracy of 82.1% with an AUROC of 83.3%.
Sensitivity was 87.7%, specificity was 76.4%, and F1-score was 83.3%.
Key predictors included PR and ER expression, Ki67, and baseline MRI features.

Cite This Study

Azmat et al. (2026) studied this question.

synapsesocial.com/papers/6a6af54160e2b924d3ea12fc https://doi.org/10.3390/diagnostics16152374

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Implication

Randomized trial evaluates predictive performance of machine learning using clinical data in HER2-positive breast cancer, indicating strong implications for treatment planning.

A Practical Machine Learning Model for Predicting Neoadjuvant Response in HER2-Positive Breast Cancer

Discussion

Member takes

Implication

Key Points

Cite This Study

A Practical Machine Learning Model for Predicting Neoadjuvant Response in HER2-Positive Breast Cancer

Discussion

Member takes

Implication

Key Points

Cite This Study

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