Jeonbuk National University (JBNU) College of Medicine student Lee Se-hyun(first-year medical student) was listed as the first author on a research paper published in the international neuroscience journal 『Brain Research Bulletin』.

The paper is titled 「Limbic structural markers of language delay in late-preterm children by NeuroQuant and machine learning」 and can be accessed via DOI: 10.1016/j.brainresbull.2026.111834.

It is considered an exceptional achievement for an undergraduate student to be named as first author in an SCI-level international journal. In particular, the study drew attention for using artificial intelligence (AI) to identify correlations between detailed brain volumes of preterm infants and developmental language disorders, and for developing a model capable of early prediction of language disorders based on those findings.

Under the supervision of Professor Hyun-ho Kim(Department of Pediatrics, Seoul St. Mary’s Hospital), she analyzed brain MRI data from patients in the neonatal intensive care unit at Jeonbuk National University Hospital. Using the quantitative brain MRI analysis software 'NeuroQuant', she measured volumes of individual brain regions and applied these measures to a machine-learning model to determine associations with delayed language development.

The core of the research is ‘early prediction’. Whereas previously prolonged follow-up was required to detect language development abnormalities in preterm infants, this study demonstrated that MRI data acquired immediately after birth can predict the likelihood of future developmental language disorders with high accuracy. Accordingly, the findings provide a basis for advancing the timing of therapeutic interventions to improve patient prognoses.

The study had already been recognized within the domestic academic community prior to journal publication. 2024년 it won the Best Poster Award at the Autumn Conference of the Korean Society of Medical Artificial Intelligence and the Best Paper Award at the Autumn Conference of the Korean Society of Medical Informatics, earning two top honors.

Lee Se-hyun said, “I entered medical school out of interest in neuroscience, and it is very meaningful that the medical AI research I have pursued since my premedical years has been published in an international journal”, adding “If early identification of at-risk cases can accelerate treatment, it can improve patient outcomes and reduce the burden on medical staff and caregivers”.

She added, “Going forward, I want to integrate AI technologies into diverse clinical areas such as neurological disorders and intractable tumors to produce tangible medical value”.