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Building scientific evidence is core to our development of AI systems.
Research Evidence
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AI
Breast
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Oncology
REFERENCE LIBRARY
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Journal of Clinical Oncology
Lancet Digital Health
JAMA Oncology
Radiology
Clinical Cancer Research
European Journal of Cancer
CVPR
ICCV
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MICCAI
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Publications
Breast
Mammography Breast Cancer Screening Triage Using Deep Learning: A UK Retrospective Study
AUTHOR
Sarah E. Hickman et al.
PUBLICATION
Radiology 2023
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Oncology
Artificial intelligence-powered spatial analysis of tumor-infiltrating lymphocytes for prediction of prognosis in resected colon cancer
AUTHOR
Yoojoo Lim et al.
PUBLICATION
npj Precision Oncology 2023
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Breast
Population-wide evaluation of artificial intelligence and radiologist assessment of screening mammograms
AUTHOR
Johanne Kühl1 et al.
PUBLICATION
European Radiology (2023)
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Oncology
Safety and efficacy of YBL-006, a novel anti-PD-1 antibody, in advanced solid tumors including G3 NET/NEC: results from a phase 1/2A study
AUTHOR
Keun-Wook Lee et al.
PUBLICATION
SITC 2023
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Oncology
AI-powered immune phenotyping based on programmed death ligand 1 (PD-L1) immunohistochemistry (IHC) in triple negative breast cancer (TNBC)
AUTHOR
Sangwon Shin et al.
PUBLICATION
SITC 2023
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Fragmented pattern of tumor mass is related to fibroblast activation mitigating spatial interaction between tumor and immune cells
AUTHOR
Sukjun Kim et al.
PUBLICATION
SITC 2023
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Oncology
Pan-cancer methylation analysis reveals a significant correlation of immune-desert phenotype with methylation aberrancy
AUTHOR
Sanghoon Song et al.
PUBLICATION
SITC 2023
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Oncology
Tumor-infiltrating lymphocytes in tumor microenvironment assessed by AI-powered H&E image analyzer is correlated with immunomodulatory subtype of triple-negative breast cancer
AUTHOR
Jimin Moon et al.
PUBLICATION
SITC 2023
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Oncology
Spatial analysis of tumor-infiltrating lymphocytes in tumor microenvironment in non-small cell lung cancer patients who have resistance after EGFR tyrosine kinase inhibitors
AUTHOR
Yeong Hak Bang et al.
PUBLICATION
SITC 2023
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Oncology
2330P - Pre-test prediction of multiple druggable mutations based on H&E image artificial intelligence (AI) analysis may enable more efficient clinical workflow...
AUTHOR
Junho Lee et al.
PUBLICATION
ESMO 2023
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