Accurate and reproducible invasive breast cancer detection in whole-slide images: A Deep Learning approach for quantifying tumor extent
2017 · Scientific Reports · 523 citations
https://doi.org/10.1038/srep46450
H
Hannah Gilmore
Cleveland Clinic(US)
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Hannah Gilmore is an academic researcher from Cleveland Clinic. The author has contributed to research in topics: Breast Cancer Treatment Studies & Radiomics and Machine Learning in Medical Imaging & AI in cancer detection. The author has an h-index of 36, co-authored 119 publications.
Papers by this author
worksHistoQC: An Open-Source Quality Control Tool for Digital Pathology Slides
2019 · JCO Clinical Cancer Informatics · 341 citations
https://doi.org/10.1200/cci.18.00157
Association of Peritumoral Radiomics With Tumor Biology and Pathologic Response to Preoperative Targeted Therapy for<i>HER2 (ERBB2)</i>–Positive Breast Cancer
2019 · JAMA Network Open · 325 citations
https://doi.org/10.1001/jamanetworkopen.2019.2561
Mapping the cellular and molecular heterogeneity of normal and malignant breast tissues and cultured cell lines
2010 · Breast Cancer Research · 209 citations
https://doi.org/10.1186/bcr2755
Immune Signatures Following Single Dose Trastuzumab Predict Pathologic Response to PreoperativeTrastuzumab and Chemotherapy in HER2-Positive Early Breast Cancer
2016 · Clinical Cancer Research · 117 citations
https://doi.org/10.1158/1078-0432.ccr-15-2021
Automated Tubule Nuclei Quantification and Correlation with Oncotype DX risk categories in ER+ Breast Cancer Whole Slide Images
2016 · Scientific Reports · 96 citations
https://doi.org/10.1038/srep32706
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