Jeonghyun Kang

Professor

Yonsei University College of Medicine

South Korea

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Jeonghyun Kang is a Professor at Yonsei University College of Medicine in South Korea. His research focuses on colorectal cancer, particularly in the areas of prognostic nutritional indexes, neoadjuvant therapies, and the diagnosis of lymph node metastasis using advanced imaging techniques. He has contributed significantly to understanding the impact of various clinical factors on patient outcomes in colorectal cancer.

Articles (20)

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2025

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2022

Collaborators (6)

Eun Jung Park

Professor

Yonsei University College of Medicine

SOUTH KOREA

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Seung Hyuk Baik

Head

Yonsei University Health System

SOUTH KOREA

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Sung Hak Lee

associate professor

Catholic University of Korea School of Medicine

SOUTH KOREA

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Anant Madabhushi

Robert Woodruff Professor

Emory University

UNITED STATES

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Hye Sun Lee

Yonsei University College of Medicine

SOUTH KOREA

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In Kyu Park

Seoul National University Hospital

SOUTH KOREA

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Jeonghyun Kang

Research Interests

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About

Articles (20)

Combining Preoperative and Postoperative Prognostic Nutritional Index as an Improved Prognostic Factor for Overall Survival in Patients with Colorectal Cancer

Evaluating the Impact of Induction and Consolidation Total Neoadjuvant Therapies Compared to Conventional Chemoradiotherapy for Locally Advanced Rectal Cancer: A Systematic Review and Network Meta-analysis

Multi-Task Adaptive Resolution Network for Lymph Node Metastasis Diagnosis From Whole Slide Images of Colorectal Cancer

Synergistic prognostic impact of hemoglobin and skeletal muscle index in patients with colorectal cancer

Prognostic significance of serum creatinine and sarcopenia for 5-year overall survival in patients with colorectal cancer in Korea: a comparative study

Varying clinical relevance of sarcopenia and myosteatosis according to age among patients with postoperative colorectal cancer

Sarcopenia diagnosis in patients with colorectal cancer: a review of computed tomography-based assessments and emerging ways to enhance practicality

Intracorporeal versus extracorporeal anastomosis in minimally invasive right hemicolectomy: systematic review and meta-analysis of randomized controlled trials

Skeletal muscle gauge prediction by a machine learning model in patients with colorectal cancer

ASO Visual Abstract: Machine Learning Algorithms Using Systemic Inflammatory Markers for Predicting the Oncological Outcomes of Colorectal Cancer After Surgery

Machine-Learning Algorithms Using Systemic Inflammatory Markers to Predict the Oncologic Outcomes of Colorectal Cancer After Surgery

ASO Author Reflections: Could the Application of Machine Learning Enhance the Accuracy of Prognosis Estimation Using Serum Inflammatory Markers in Colorectal Cancer Patients?

Albumin‐myosteatosis gauge as a novel prognostic risk factor in patients with non‐metastatic colorectal cancer

Prediction of Microsatellite Instability in Colorectal Cancer Using a Machine Learning Model Based on PET/CT Radiomics

Vision Transformers for Computational Histopathology

Combined impact of myosteatosis and liver steatosis on prognosis in stage I–III colorectal cancer patients

Reply to Letter by Min Zou et al.: Comment on “Association of Albumin–Bilirubin Grade and Myosteatosis with its Prognostic Significance for Patients with Colorectal Cancer”

Spatial analysis of tumor‐infiltrating lymphocytes in histological sections using deep learning techniques predicts survival in colorectal carcinoma

ASO Author Reflections: Albumin–Bilirubin Grade and Myosteatosis as Potential Cancer Cachexia-Related Indicators in Patients with Colorectal Cancer

ASO Visual Abstract: Association Between Albumin–Bilirubin Grade and Myosteatosis and Its Prognostic Significance for Patients with Colorectal Cancer

Collaborators (6)

Eun Jung Park

Seung Hyuk Baik

Sung Hak Lee

Anant Madabhushi

Hye Sun Lee

In Kyu Park

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