Publications
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AI를 설계합니다.
Tumor-infiltrating lymphocyte enrichment predicted by CT radiomic analysis is associated with clinical outcomes of immune checkpoint inhibitor in non-small cell lung cancer
Artificial intelligence (AI)-powered pathology image analysis merged with spatial transcriptomics reveals distinct TIGIT expression in the immune-excluded tumor-infiltrating lymphocytes
Artificial intelligence-powered human epidermal growth factor receptor 2 (HER2) analyzer in breast cancer as an assistance tool for pathologists to reduce interobserver variation
Observer Performance Study to Examine the Feasibility of the AI-powered PD-L1 Analyzer to Assist Pathologists’ Assessment of PD-L1 Expression Using Tumor Proportion Score in Non-Small Cell Lung Cancer
Need of pretreatment support of breast cancer patient caregivers compared to patients.
Robust artificial intelligence-powered imaging biomarker based on mammography for risk prediction of breast cancer.
Safety and efficacy of YBL-006, an anti-PD-1 monoclonal antibody in advanced solid tumors: a phase I study
Tumor-infiltrating lymphocyte enrichment predicted by CT radiomic analysis is associated with clinical outcomes of immune checkpoint inhibitor in non-small cell lung cancer
The Inflamed Immune Phenotype (IIP): a clinically actionable artificial intelligence (AI)-based biomarker predictive of immune checkpoint inhibitor (ICI) outcomes across >16 primary tumor types
Trastuzumab plus FOLFOX for Gemcitabine/Cisplatin refractory HER2-positive biliary tract cancer: a multi-institutional phase II trial of the Korean Cancer Study Group (KCSG-HB19-14)
Artificial intelligence (AI)-powered pathology image analysis merged with spatial transcriptomics reveals distinct TIGIT expression in the immune-excluded tumor-infiltrating lymphocytes
Artificial Intelligence (AI) - powered spatial analysis of tumor-infiltrating lymphocytes (TIL) for prediction of response to neoadjuvant chemotherapy (NAC) in triple negative breast cancer (TNBC)