Mr. Hyungbok Lee | Neonatal | Best Researcher Award

Profile

ORCID

Education

Hyungbok Lee pursued his academic journey with a strong focus on nursing and healthcare innovation, culminating in a doctorate in Nursing Informatics from Seoul National University College of Nursing. His education emphasized the intersection of clinical practice and informatics, preparing him to address pressing challenges in healthcare systems. During his studies, he developed expertise in machine learning, clinical decision support systems, and predictive modeling, applying these concepts to enhance patient care and safety. His doctoral research focused on harnessing artificial intelligence to develop explainable models capable of supporting healthcare professionals in emergency and clinical settings. Through rigorous training, he cultivated a balance of clinical insight, data science proficiency, and nursing leadership. His academic background not only equipped him with technical knowledge but also nurtured his ability to translate research findings into practical solutions, bridging the gap between nursing science, informatics, and patient-centered healthcare practices at institutional and policy-making levels.

Experience

Professionally, Hyungbok Lee has built a distinguished career as Unit Manager at Seoul National University Hospital, where he integrates clinical leadership with innovative research. His role involves managing nursing operations while fostering a culture of evidence-based practice and data-driven healthcare solutions. He has extensive experience in designing and implementing decision support tools, patient safety initiatives, and quality improvement programs within emergency and critical care environments. His collaborative research with interdisciplinary teams has yielded influential publications on topics ranging from workplace violence prediction to patient flow management and risk factor identification using machine learning approaches. By engaging with both clinical staff and researchers, he ensures that advanced technologies such as explainable AI are practically applicable in real-world healthcare settings. His experience reflects a unique blend of administrative leadership, clinical expertise, and academic scholarship, positioning him as a leading figure in advancing nursing informatics and shaping the future of patient care systems.

Awards and Honors

Throughout his career, Hyungbok Lee has been recognized for his significant contributions to the fields of nursing informatics and healthcare innovation. His publications in high-impact international journals and participation in global conferences have brought him acclaim within both the nursing and informatics communities. His collaborative research on explainable artificial intelligence and clinical decision-making has been acknowledged as pioneering, earning him invitations to present at prestigious academic platforms. His dedication to improving emergency care efficiency and workplace safety has been widely valued in professional healthcare circles. His achievements demonstrate not only scholarly excellence but also real-world impact, leading to recognition from peers and institutions alike. These honors reflect his ability to merge nursing practice with cutting-edge technology, advancing both patient safety and healthcare outcomes. His record of accomplishments highlights his role as a thought leader and innovator, inspiring future nursing professionals and researchers to embrace informatics-driven approaches in healthcare

Research Focus

Hyungbok Lee’s research primarily centers on the integration of artificial intelligence and machine learning into healthcare systems to enhance clinical decision support. He is particularly focused on developing explainable AI tools that not only provide accurate predictions but also deliver transparent reasoning to support clinician trust and adoption. His studies have examined critical issues such as predicting patient length of stay in intensive care, identifying risk factors for obesity, and forecasting workplace violence in emergency departments. A key theme in his work is balancing data privacy with utility in clinical data analysis, reflecting his commitment to ethical and responsible use of health data. By collaborating with interdisciplinary teams, he advances research that bridges the gap between technological innovation and practical application in clinical settings. His focus remains on improving patient outcomes, optimizing healthcare efficiency, and creating supportive tools that empower nurses and physicians to make informed, timely decisions.

Publications

Title: A Comparison of Data Sampling Techniques for Predicting Postoperative Delirium in Neurosurgery
Year: 2025

Title: Analysis of Factors Affecting Postoperative Delirium in General Surgery: Applying Machine Learning
Year: 2025

Title: Predicting Postoperative Delirium in Orthopedic Surgery Using Explainable Artificial Intelligence
Year: 2025

Title: Neonatal Jaundice Requiring Phototherapy Risk Factors in a Newborn Nursery: Machine Learning Approach
Year: 2025

Title: Exploring the Tradeoff Between Data Privacy and Utility with a Clinical Data Analysis Use Case
Year: 2024

Title: Essential Properties and Explanation Effectiveness of Explainable Artificial Intelligence in Healthcare: A Systematic Review
Year: 2023

Title: Factors Affecting the Length of Stay in the Emergency Department for Critically Ill Patients Transferred to Regional Emergency Medical Center
Year: 2023

Conclusion

Hyungbok Lee is a visionary nursing leader and researcher whose work in nursing informatics and artificial intelligence continues to transform healthcare by bridging clinical expertise with technological innovation, driving advancements in decision support systems, predictive modeling, patient safety, and healthcare efficiency while inspiring future generations of nursing professionals to embrace data-driven approaches for better patient outcomes and stronger healthcare systems.