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

Breast Cancer (398) Clinical Information and Decision Making (3523) Decision Support for Health Professionals (2113) Innovations and Technology in Cancer Care (662) Innovations and Technology for Cancer Prevention and Screening (258) Machine Learning (3036)

Published on in Vol 9 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/46474, first published .
Laptop displaying NILS Non Invasive Lymph Node Staging calculator with patient data and probability graph.

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
Article Authors Cited by (2) Tweetations (2) Metrics

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
  2. Allfelt A, Bendahl P, Dihge L, Ohlsson M, Rydén L, Skarping I. Human factors validation study of an artificial neural network‑based preoperative decision‑support tool for noninvasive lymph node staging (NILS) in women with primary breast cancer (ISRCTN99301435). BMC Cancer 2026;26(1) View