Cited by 156AI in cancer detectionRadiomics and Machine Learning in Medical ImagingBreast Cancer Treatment Studies

Morphological and molecular breast cancer profiling through explainable machine learning

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Binder, Alexander, Bockmayr, Michael, Hägele, Miriam, Wienert, Stephan, Heim, Daniel, Hellweg, Katharina, Ishii, Masaru, Stenzinger, Albrecht +4 more·2021·Nature Machine Intelligence

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Crossref · 10.1038/s42256-021-00303-4

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40 of 40 references verified0 citation errors · 0 not checkable

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  • Other efforts have used AI on H&E images to predict TIL presence and PD-L1 expression status in breast cancer.

    “Other efforts have used AI on H&E images to directly predict TIL presence (85,86), a notable prognostic and predictive biomarker in breast cancer, and programmed cell death ligand 1 (PD-L1) expression status, a predictive biomarker for immunotherapies (87).”

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Authors
Binder, A., Bockmayr, M., Hägele, M., Wienert, S., Heim, D., Hellweg, K., Ishii, M., Stenzinger, A., Hocke, A., Denkert, C., Müller, K.-R., & Klauschen, F.
Affiliations
  • Singapore University of Technology and Design (SG)
  • University Medical Center Hamburg-Eppendorf (DE)
  • Technische Universität Berlin (DE)
  • Berlin Institute of Health at Charité - Universitätsmedizin Berlin (DE)
  • The University of Osaka (JP)
  • Heidelberg University (DE)
  • Philipps University of Marburg (DE)
  • Korea University (KR)
Corresponding author
  • Müller, Klaus-Robert
  • Klauschen, Frederick
Venue
Nature Machine Intelligence
Published
2021-03-08
Volume
3
Issue
4
Pages
355-366
ISSN
2522-5839 (ISSN-L)
OpenAlex
W3135345798
Cited by
156
References
40
Citations by year
2026: 13 · 2025: 31 · 2024: 32 · 2023: 31 · 2022: 28 · 2021: 21
FWCI
9.90
Type
journal article
Language
en
Open access
Locations
  • Nature Machine Intelligence (publishedVersion)
  • NORA - Norwegian Open Research Archives (submittedVersion, other-oa)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › AI in cancer detection
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Radiomics and Machine Learning in Medical Imaging
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Breast Cancer Treatment Studies
Keywords
breast cancer, histopathology, cancer cell detection, tumor-infiltrating lymphocytes, DNA methylation prediction, gene expression prediction, copy number variation, somatic mutations, protein expression prediction, explainable AI, precision medicine, cancer diagnosis

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