Jung Keun Hyun

Professor

Dankook University - Cheonan Campus

South Korea

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About

Jung Keun Hyun is a Professor at Dankook University - Cheonan Campus in South Korea. His research areas include biomechanics, biomedical monitoring, and regenerative medicine, as evidenced by recent publications focusing on topics such as gait recovery post-arthroplasty, muscle atrophy prevention, and innovative diagnostic methods for sarcopenia. He is also involved in the development of advanced bioadhesives and biodegradable electronic devices for neural interfacing and nerve regeneration.

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Collaborators (12)

Seongjun Park

Assistant Professor

KAIST

SOUTH KOREA

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Won Sang Yoo

Assistant professor

Dankook University - Cheonan Campus

SOUTH KOREA

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Taekyung Kim

Research Professor

Sungkyunkwan University

SOUTH KOREA

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Daeshik Kang

SOUTH KOREA

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Jung-Hwan Lee

Professor

Dankook University College of Dentistry

SOUTH KOREA

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Dong-Hwee Kim

Associate Professor

Korea University

SOUTH KOREA

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Kapil D Patel

University of Bristol

UNITED KINGDOM

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Seongchan Kim

Assistant Professor

Gyeongsang National University

SOUTH KOREA

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Jennifer Olmos Buitrago

Teaching and Research Faculty (PDI)

Universitat Internacional de Catalunya

SPAIN

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Youngmee Jung

Korea University of Science and Technology

SOUTH KOREA

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sungryul shim

Professor

Konyang University College of Medicine

SOUTH KOREA

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Seong Jae Lee

Dankook University

SOUTH KOREA

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Jung Keun Hyun

Research Interests

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Articles (25)

A Pressure-Sensitive, Repositionable Bioadhesive for Instant, Atraumatic Surgical Application on Internal Organs

Predictive Factors for Gait Recovery in Patients Undergoing Total Hip Arthroplasty: A Propensity Score Weighting Analysis

Lonafarnib Protects Against Muscle Atrophy Induced by Dexamethasone

Enhancing the Diagnosis of Sarcopenia Through Low-Dose Chest CT and Artificial Intelligence-Based Segmentation: Optimizing Resource Utilization in Healthcare

Association between neural stem/progenitor cells and biomaterials in spinal cord injury therapies: A systematic review and network meta-analysis

Integrated Machine Learning Approach for the Early Prediction of Pressure Ulcers in Spinal Cord Injury Patients

A biodegradable and self-deployable electronic tent electrode for brain cortex interfacing

Hypersensitive Meta-Crack Strain Sensor for Real-Time Biomedical Monitoring

A Fully Biodegradable and Ultra‐Sensitive Crack‐Based Strain Sensor for Biomechanical Signal Monitoring

Electroconductive and mechano-competent PUCL@CNT nanohybrid scaffolds guiding neuronal specification of neural stem/progenitor cells

Electroceuticals for Regeneration of Long Nerve Gap Using Biodegradable Conductive Conduits and Implantable Wireless Stimulator

A Deep Learning Approach for Predicting Pressure Ulcers from Time-Series Electronic Medical Records

Delivery of Induced Neural Stem Cells Through Mechano‐Tuned Silk–Collagen Hydrogels for the Recovery of Contused Spinal Cord in Rats

Quantitative Analysis in Cervical Spinal Cord Injury Patients Using Diffusion Tensor Imaging and Tractography

The Time Sequence of Gene Expression Changes after Spinal Cord Injury

Prediction of Poststroke Depression Based on the Outcomes of Machine Learning Algorithms

Enhanced Recognition of Amputated Wrist and Hand Movements by Deep Learning Method Using Multimodal Fusion of Electromyography and Electroencephalography

Self-assembling peptide gels promote angiogenesis and functional recovery after spinal cord injury in rats

Micropattern-based nerve guidance conduit with hundreds of microchannels and stem cell recruitment for nerve regeneration

Prediction of Diabetic Neuropathy Using Machine Learning Techniques

Prediction of Diabetic Sensorimotor Polyneuropathy Using Machine Learning Techniques

Predictors of Aspiration Pneumonia in the Elderly With Swallowing Dysfunction: Videofluoroscopic Swallowing Study

Predictors of Aspiration Pneumonia in the Elderly With Swallowing Dysfunction: Videofluoroscopic Swallowing Study

Exercise Ameliorates Spinal Cord Injury by Changing DNA Methylation

Effectiveness of Chin Tuck on Laryngeal Penetration: Quantitative Assessment

Collaborators (12)

Seongjun Park

Won Sang Yoo

Taekyung Kim

Daeshik Kang

Jung-Hwan Lee

Dong-Hwee Kim

Kapil D Patel

Seongchan Kim

Jennifer Olmos Buitrago

Youngmee Jung

sungryul shim

Seong Jae Lee

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