Multimodal Artificial Intelligence Model From Baseline Histopathology Adds Prognostic Information for Distant Recurrence Assessment in Hormone Receptor–Positive/Human Epidermal Growth Factor Receptor 2–Negative Early Breast Cancer
Year: 2025
Type: article
Source: JCO Clinical Cancer Informatics
DOI: 10.1200/cci-24-00287
Authors: Daniel Kates-Harbeck, Hans Kreipe, Oleg Gluz, Matthias Christgen, Sherko Kuemmel, Monika Graeser, Ulrike Nitz, Sven Mahner, Doris Mayr, Rachel Wuerstlein, Akinori Mitani, Jingbin Zhang, Hans Pinckaers, Gijs Smit, Yi Ren, Songwan Joun, Jacqueline Griffin, Nancy Lin, Felix Feng, Andre Esteva, Ronald Kates, Nadia Harbeck
Institutions: LMU Klinikum, Women‘s Healthcare Group, Ludwig-Maximilians-Universität München, Leipzig University, Medizinische Hochschule Hannover, Kliniken Essen-Mitte, Universität Hamburg, University Medical Center Hamburg-Eppendorf, Pathologisches Institut, University of California, San Francisco
Language: English
Topic: AI in cancer detection
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: closed
OpenAlex ID: W4416524037