Professor Shin-hyuk Kang wins academic award for AI-driven brain tumor diagnosis

Professor Shin-hyuk Kang of Korea University Anam Hospital has received an academic award from the Korean Neurosurgical Society. The award recognizes his research on using AI-augmented confocal laser endomicroscopy for rapid intraoperative diagnosis of brain tumors.

Traditional frozen section testing typically takes approximately 30 minutes, which can limit real-time decision-making during surgery. In a multi-center clinical study involving 376 patients and 461 tissue samples, the research team demonstrated that the confocal laser endomicroscopy method achieved a 94% diagnostic accuracy—2% higher than traditional methods. Furthermore, the median time to reach a diagnosis was 5 minutes and 56 seconds, reducing the wait time by roughly 20 minutes.

The AI diagnostic model also showed high performance, with 94% accuracy in identifying tumors and 88% accuracy in diagnosing tumor subtypes. The team's digital tissue biopsy platform, ‘cCeLL’, has recently received US FDA approval. Ongoing collaborative research involves institutions such as Harvard University and the University of Pennsylvania Hospital.