Early diagnosis of Alzheimer’s disease is crucial to stall the deterioration of brain function, but conventional diagnostic methods require complicated analytical procedures or inflict acute pain on the patient. Then, label-free Surface-enhanced Raman spectroscopy (SERS) analysis of blood-based biomarkers is a convenient alternative to rapidly obtain spectral information from biofluids. However, despite the rapid acquisition of spectral information from biofluids, it is challenging to distinguish spectral features of biomarkers due to interference from biofluidic components. Here, we investigate a deep learning-assisted, SERS-based platform for separate analysis of blood-based amyloid β (1–42) and metabolites, enabling the diagnosis of Alzheimer’s disease.
This is collaboration work with Prof. Yeon Sik Jung’s group at Department of Materials Science and Engineering, KAIST.
Related publications
1. M Kim, S Huh, HJ park, SH Cho, MY Lee, S Jo, YS Jung, Surface-Functionalized SERS Platform for Deep Learning-Assisted Diagnosis of Alzheimer’s Disease, Biosensors and Bioelectronics, 251, May 2024, [LINK] [PDF]
