Researchers from Kookmin University's Department of Chemistry Develop AI-Based ‘Precision Diagnosis’ Technology for Stomach Cancer
Combining autofluorescence spectroscopy with deep learning technology... improving gastric cancer diagnosis accuracy
- 26.03.12 / 홍유민
▲ Right: Dr. Jang Jin-il, Department of Chemistry, Kookmin University
The image on the left is concept art created by AI to support the research content.
Dr. Jang Jin-il of the Department of Chemistry at Kookmin University (President Jeong Seung Ryul) has developed a next-generation diagnostic technology that precisely identifies surgically excised gastric cancer tissue by integrating artificial intelligence (AI) and spectroscopy technology. In gastric cancer diagnosis, accurately distinguishing the boundaries of cancerous tissue and confirming the presence of cancer cell invasion directly impacts patient prognosis, leading to a consistent demand for more reliable identification technology.
Dr. Jang participated as a core researcher in Professor Kim Hyung Min's team and conducted joint research with the National Cancer Center research team. He led the system integration and advancement to overcome the limitations of existing autofluorescence spectroscopy, including ▲ measurement variations between devices ▲ damage to biological samples ▲ and complex fluorescence signal interpretation.
▲ Materials related to fluorescent signals
The research team enhanced diagnostic reliability by reducing measurement deviations caused by equipment differences. They achieved this through Dr. Jang's spectrum transfer model, which calibrates data acquired from low-performance equipment to the level of high-performance equipment. Furthermore, Dr. Jang successfully designed and built a specialized cooling chamber to prevent sample damage during analysis, effectively resolving the issue of biological samples undergoing deformation during the process. Furthermore, by applying a deep learning model to precisely classify tissue images, the accuracy of distinguishing cancerous tissue from normal tissue was improved.
Professor Kim Hyung Min, who led the joint research, stated, “This study is an achievement born from Dr. Jang Jin-il's deep understanding of analytical chemistry and the creative fusion of AI technology,” adding, “We plan to further advance the technology into a cancer diagnostic equipment system and accelerate its clinical application.”
The research findings were published online on March 4th in ‘Analytical Chemistry’, a globally authoritative journal in the field of analytical chemistry. Researchers Kook Myeong-Cherl and Yoon Hong Man from the National Cancer Center participated as co-researchers in this study.
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This content is translated from Korean to English using the AI translation service DeepL and may contain translation errors such as jargon/pronouns. If you find any, please send your feedback to kookminpr@kookmin.ac.kr so we can correct them.
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Researchers from Kookmin University's Department of Chemistry Develop AI-Based ‘Precision Diagnosis’ Technology for Stomach Cancer Combining autofluorescence spectroscopy with deep learning technology... improving gastric cancer diagnosis accuracy |
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2026-03-12
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▲ Right: Dr. Jang Jin-il, Department of Chemistry, Kookmin University The image on the left is concept art created by AI to support the research content.
Dr. Jang Jin-il of the Department of Chemistry at Kookmin University (President Jeong Seung Ryul) has developed a next-generation diagnostic technology that precisely identifies surgically excised gastric cancer tissue by integrating artificial intelligence (AI) and spectroscopy technology. In gastric cancer diagnosis, accurately distinguishing the boundaries of cancerous tissue and confirming the presence of cancer cell invasion directly impacts patient prognosis, leading to a consistent demand for more reliable identification technology.
Dr. Jang participated as a core researcher in Professor Kim Hyung Min's team and conducted joint research with the National Cancer Center research team. He led the system integration and advancement to overcome the limitations of existing autofluorescence spectroscopy, including ▲ measurement variations between devices ▲ damage to biological samples ▲ and complex fluorescence signal interpretation.
▲ Materials related to fluorescent signals
The research team enhanced diagnostic reliability by reducing measurement deviations caused by equipment differences. They achieved this through Dr. Jang's spectrum transfer model, which calibrates data acquired from low-performance equipment to the level of high-performance equipment. Furthermore, Dr. Jang successfully designed and built a specialized cooling chamber to prevent sample damage during analysis, effectively resolving the issue of biological samples undergoing deformation during the process. Furthermore, by applying a deep learning model to precisely classify tissue images, the accuracy of distinguishing cancerous tissue from normal tissue was improved.
Professor Kim Hyung Min, who led the joint research, stated, “This study is an achievement born from Dr. Jang Jin-il's deep understanding of analytical chemistry and the creative fusion of AI technology,” adding, “We plan to further advance the technology into a cancer diagnostic equipment system and accelerate its clinical application.”
The research findings were published online on March 4th in ‘Analytical Chemistry’, a globally authoritative journal in the field of analytical chemistry. Researchers Kook Myeong-Cherl and Yoon Hong Man from the National Cancer Center participated as co-researchers in this study.
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