Researchers from Korea University's Chemistry Department, led by Dr. Jang Jin-il in collaboration with Professor Kim Hyung-min and the National Cancer Center, have developed a next-generation diagnostic technology that combines artificial intelligence with spectroscopy to accurately differentiate between stomach cancer tissues. The ability to accurately distinguish the boundaries of cancer tissues and confirm the invasion of cancer cells is critical for patient prognosis, necessitating more reliable diagnostic methods. This technology addresses existing challenges in self-fluorescent spectroscopy, which have hindered progress due to measurement discrepancies between equipment, damage to biological samples, and difficulties in interpreting complex fluorescence signals.

The innovative system developed by the research team corrects data obtained from low-performance equipment to a high-performance standard using a spectral transfer model implemented by Dr. Jang. This enhancement significantly reduces measurement discrepancies and improves the diagnostic reliability of stomach cancer identification. To counteract the issue of biological sample deformation during analysis, Dr. Jang also designed a special cooling chamber to effectively prevent sample damage. Additionally, the application of deep learning models has further increased the accuracy of distinguishing between cancerous and normal tissues from histological images.

Professor Kim Hyung-min noted that this research exemplifies the innovative fusion of Dr. Jang's deep understanding of analytical chemistry and AI technology. Looking ahead, Kim plans to advance the technology further into a comprehensive cancer diagnostic system and accelerate its clinical application. This significant achievement was published on March 4 in the online edition of the prominent analytical chemistry journal, 'Analytical Chemistry', with contributions from researcher Kim Gyeong-cheol and Yoon Hong-man from the National Cancer Center involved in the joint study.