Machine learning model for the prediction of pathological complete response after neoadjuvant chemotherapy in breast cancer

Authors

Benedikt Schäfgen
André Pfob (ORCID: https://orcid.org/0000-0001-6140-9895)
Lie Cai (ORCID: https://orcid.org/0009-0002-3899-3346)
Eva Reisig
Maria Müller

Publication Details

Journal: BMC Cancer
Published: 2026-10-08
DOI: https://doi.org/10.1186/s12885-026-17115-7
Primary Topic: Breast Cancer Treatment Studies
Type: article
Field-Weighted Citation Impact: 0.00

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article

Machine learning model for the prediction of pathological complete response after neoadjuvant chemotherapy in breast cancer

Benedikt Schäfgen, André Pfob, Lie Cai, Eva Reisig et al.

Oct 8, 2026

BMC Cancer

Breast Cancer Treatment Studies

article

Machine learning model for the prediction of pathological complete response after neoadjuvant chemotherapy in breast cancer

Benedikt Schäfgen, André Pfob, Lie Cai, Eva Reisig, Maria Müller

October 8, 2026article en

Abstract

No abstract available for this paper.

BMC Cancer

Openalex Percentile: Top 18%

Breast Cancer Treatment Studies

DOI Open Access PDF OpenAlex

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Machine learning model for the prediction of pathological complete response after neoadjuvant chemotherapy in breast cancer — Benedikt Schäfgen, André Pfob, et al. · BMC Cancer (2026) | TGRS Research Map | TGRS