A machine learning-based algorithm to eliminate breast and axillary surgery in patients with breast cancer and pathological complete response after neoadjuvant chemotherapy

Ann Transl Med. 2023 Oct 25;11(11):397. doi: 10.21037/atm-23-689. Epub 2023 Mar 6.

Alexandre de Nonneville^#^{1

2}, Laurys Boudin^#^{1

3}, Gilles Houvenaeghel⁴, Anthony Gonçalves², François Bertucci^{1

2}

¹ Laboratory of Predictive Oncology, Centre de Recherche en Cancérologie de Marseille, Institut Paoli-Calmettes, INSERM UMR1068, CNRS UMR725, Equipe Labellisée Ligue Nationale Contre Le Cancer, Marseille, France.
² Department of Medical Oncology, CRCM, Institut Paoli‑Calmettes, Aix-Marseille Univ, CNRS, INSERM, Marseille, France.
³ Department of Medical Oncology, Sainte-Anne Military Teaching Hospital, Toulon, France.
⁴ Department of Surgical Oncology, CRCM, Institut Paoli‑Calmettes, Aix-Marseille Univ, CNRS, INSERM, Marseille, France.

^# Contributed equally.

No abstract available

Keywords: Breast cancer (BC); de-escalation; machine learning; neoadjuvant chemotherapy (NACT); pathological response.

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