Du Hyun Ro

Professor

Seoul National University College of Medicine

South Korea

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About

Du Hyun Ro is a Professor at Seoul National University College of Medicine in South Korea. His research focuses on knee osteoarthritis, including decision-making processes, structural changes, and the application of machine learning in predicting disease progression and automated classification. He has authored several recent articles addressing innovative methodologies for evaluating knee conditions and the use of deep learning in radiographic assessments.

Articles (20)

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2025

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2023

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2023

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2023

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2022

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2022

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2022

Collaborators (5)

Byung Sun Choi

Seoul National University Hospital

SOUTH KOREA

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Myung Chul Lee

Seoul National University College of Medicine

SOUTH KOREA

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Yong-Beom Park

Chung-Ang University

SOUTH KOREA

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Joong Il Kim

SOUTH KOREA

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Hyuk-Soo Han

SOUTH KOREA

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Du Hyun Ro

Research Interests

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About

Articles (20)

Current status and prospects of shared decision-making for severe knee osteoarthritis in Korea: a narrative review

Longitudinal correlation between X‐ray and MRI findings in medial compartment knee osteoarthritis: Insights into early cartilage loss and structural changes

External Validation of a Novel Landmark-Based Deep Learning Automated Tibial Slope Measurement Algorithm Applied on Short Radiographs Obtained in Patients With ACL Injuries

Correction: Accurate, automated classification of radiographic knee osteoarthritis severity using a novel method of deep learning: Plug‑in modules

Association of radiographic structure deformity phenotypes of knee OA to clinical symptoms and risk for progression: Proposing a modification of Kellgren-Lawrence grade - Data from the Osteoarthritis Initiative and the MOST study

Machine learning‐based prediction of contralateral knee osteoarthritis development using the Osteoarthritis Initiative and the Multicenter Osteoarthritis Study dataset

Coronal Plane Alignment of the Knee (CPAK) Type Shifts Toward Constitutional Varus with Increasing Kellgren and Lawrence Grade

Deep learning for automated hip fracture detection and classification

Risk factors of recurrent periprosthetic joint infection of the knee after two-stage reimplantation

Development of the machine learning model that is highly validated and easily applicable to predict radiographic knee osteoarthritis progression

Effectiveness of Robotic Arm-Assisted Total Knee Arthroplasty on Transfusion Rate in Staged Bilateral Surgery

High‐resolution knee plain radiography image synthesis using style generative adversarial network adaptive discriminator augmentation

Deep learning-based landmark recognition and angle measurement of full-leg plain radiographs can be adopted to assess lower extremity alignment

Development of Prediction Model Using Machine-Learning Algorithms for Nonsteroidal Anti-inflammatory Drug-Induced Gastric Ulcer in Osteoarthritis Patients: Retrospective Cohort Study of a Nationwide South Korean Cohort

Patella Cartilage Status Does Not Affect the Clinical Outcomes of Non-resurfaced Patella in Mobile-Bearing Total Knee Arthroplasty

Rectangular-Tunnel Anterior Cruciate Ligament Reconstruction Using Quadriceps Tendon-Patellar Bone Autograft Can Reduce Early Donor Site Morbidity While Maintaining Comparable Short-term Clinical Outcomes

Titanium Alloy Knee Implant Is Associated with Higher Bone Density over Cobalt Chromium: A Prospective Matched-Pair Case-Control Study

Deep Learning-Based Muscle Segmentation and Quantification of Full-Leg Plain Radiograph for Sarcopenia Screening in Patients Undergoing Total Knee Arthroplasty

Automated Detection of Surgical Implants on Plain Knee Radiographs Using a Deep Learning Algorithm

Single shot adductor canal block combined with intravenous patient-controlled analgesia can be effective as continuous adductor canal block in reducing opioid consumption and breakthrough pain after total knee arthroplasty

Collaborators (5)

Byung Sun Choi

Myung Chul Lee

Yong-Beom Park

Joong Il Kim

Hyuk-Soo Han

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