賴昆佑
簡汎清

This research focuses on analyzing human plasma associated with four cancers (breast, endometria, lung, pancreas), using the surface-enhanced Raman spectroscopy (SERS) integrated with machine learning for prediction and classification. The SERS structure comprises multiple InGaN quantum wells. According to the test results of 69 clinical cases (10 cases of breast cancer, 10 cases of endometrial cancer, 29 cases of lung cancer, 10 cases of pancreatic cancer, and 10 cases of health control), our technique can quickly identify the types of cancer with the average prediction accuracy of 96%.