An outlier removal method based on PCA-DBSCAN for blood-SERS data analysis
Miaomiao Liu, Tingyin Wang, Qiyi Zhang, Changbin Pan, Shuhang Liu, Yuanmei Chen, Duo Lin, Shangyuan Feng
Abstract
1-score. This paper introduces a new outlier removal method that significantly improves the performance of the SERS cancer screening model. Moreover, the proposed method serves as inspiration for outlier detection in other fields, such as biomedical research, environmental monitoring, manufacturing, quality control, and hazard prediction.
Topics & Concepts
OutlierRaman spectroscopySurface-enhanced Raman spectroscopyComputer sciencePattern recognition (psychology)DBSCANPrincipal component analysisAnomaly detectionArtificial intelligenceData miningAnalytical Chemistry (journal)ChemistryMaterials scienceBiological systemChromatographyCluster analysisRaman scatteringPhysicsOpticsBiologyCanopy clustering algorithmCorrelation clusteringSpectroscopy Techniques in Biomedical and Chemical ResearchGold and Silver Nanoparticles Synthesis and ApplicationsLaser-induced spectroscopy and plasma