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This paper is in the following e-collection/theme issue:

Breast Cancer (315) Machine Learning (2238) Innovations and Technology for Cancer Prevention and Screening (212) Clinical Information and Decision Making (2076) Decision Support for Health Professionals (1644) Innovations and Technology in Cancer Care (572)

Published on in Vol 9 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/46474, first published .
Noninvasive Staging of Lymph Node Status in Breast Cancer Using Machine Learning: External Validation and Further Model Development

Noninvasive Staging of Lymph Node Status in Breast Cancer Using Machine Learning: External Validation and Further Model Development

Noninvasive Staging of Lymph Node Status in Breast Cancer Using Machine Learning: External Validation and Further Model Development

Authors of this article:

Malin Hjärtström1 Author Orcid Image ;   Looket Dihge2, 3 Author Orcid Image ;   Pär-Ola Bendahl1 Author Orcid Image ;   Ida Skarping1, 4 Author Orcid Image ;   Julia Ellbrant2, 5 Author Orcid Image ;   Mattias Ohlsson6, 7 Author Orcid Image ;   Lisa Rydén2, 8 Author Orcid Image
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Journals

  1. Mosquim Junior S, Zamore M, Vallon-Christersson J, Rydén L, Levander F. Multiomic profiling of ER-positive HER2-negative breast cancer reveals markers associated with metastatic spread. Breast Cancer Research 2026;28(1) View