关键词: 机器学习, SERS光谱, 肝癌诊断, 学科交叉, 人才培养

Abstract: Against the backdrop of the 2024 Nobel Prize in Physics, which is a typical physicscomputer science crossover, takes the surfaceenhanced Raman scattering (SERS) spectroscopy technique involved in university physics experiments as an entry point, and guides undergraduate medical students to compare the differences in serum SERS spectra between the healthy control group and the hepatocellular carcinoma group by means of physical spectroscopy and to trace back the vibrational bonds, so as to explore the differences in serum levels of The differences in serum levels of AFP and CA199 were explored between the two groups. Further investigation of this ‘medicinephysicscomputing’ crossdisciplinary case on the training of crossdisciplinary physics talents is very useful for broadening the reform ideas of innovative crossdisciplinary physics talents training mode.

Key words: Machine learning, SERS spectroscopy, liver cancer diagnosis, discipline intersection, talent development