CHAN KYO KIM

Professor

Samsung Medical Center

South Korea

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Dr. Chan Kyo Kim is a Professor at Samsung Medical Center, South Korea. His research focuses on urological imaging and cancer prediction, particularly in relation to prostate and bladder cancers. Recent publications include studies on prostate health index density, MRI-based measurements, and the application of deep learning in cancer prognosis.

CHAN KYO KIM

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Articles (16)

Utility of Prostate Health Index Density for Biopsy Strategy in Biopsy‐Naïve Patients With PI‐RADS v2.1 Category 3 Lesions

The utility of two-dimensional shear wave elastography for predicting prostate cancer: a preliminary study

Novel Multiparametric Magnetic Resonance Imaging-Based Deep Learning and Clinical Parameter Integration for the Prediction of Long-Term Biochemical Recurrence-Free Survival in Prostate Cancer after Radical Prostatectomy

Inter-method agreement between wash-in and wash-out computed tomography for characterizing hyperattenuating adrenal lesions as adenomas or non-adenomas

Prostate Imaging Reporting and Data System (PI-RADS) v 2.1: Overview and Critical Points

Proposed MRI-based membranous urethral length measurement standardization: a step to pave the way for clinical implementation?

Computed tomography-based prediction model for identifying patients with high probability of non-muscle-invasive bladder cancer

Neoadjuvant Nivolumab Plus Gemcitabine/Cisplatin Chemotherapy in Muscle-Invasive Urothelial Carcinoma of the Bladder

[Prostate Imaging Reporting and Data System (PI-RADS) v 2.1: Overview and Critical Points]

Prostate imaging-reporting and data system version 2 has improved biopsy tumor grade accuracy: a single, tertiary institutional experience

Blood oxygenation level-dependent MRI at 3T for differentiating prostate cancer from benign tissue: a preliminary experience

Blood oxygenation level-dependent MRI at 3T for differentiating prostate cancer from benign tissue: a preliminary experience

Magnetic resonance imaging-based texture analysis for the prediction of postoperative clinical outcome in uterine cervical cancer

Magnetic resonance imaging-based texture analysis for the prediction of postoperative clinical outcome in uterine cervical cancer

3D multi-scale residual fully convolutional neural network for segmentation of extremely large-sized kidney tumor

A Retrospective Study of First-Line Therapy Involving Immune Checkpoint Inhibitors in Patients With Poor Risk Metastatic Renal Cell Carcinoma

Collaborators (2)

Hyunjin Park

Sung Yoon Park

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