ArticleBiomedical optics express2018
Label-free detection of nasopharyngeal and liver cancer using surface-enhanced Raman spectroscopy and partial lease squares combined with support vector machine.
Article in Biomedical optics express, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- Gold- or Silver-Nanoparticle SERS Platforms for Plasma-Based Diagnostics and AI-Driven Analysis.Sensors (Basel, Switzerland) · 2026Review
- Raman Spectroscopic Signatures of Hepatic Carcinoma: Progress and Future Prospect.International journal of molecular sciences · 2026Review
- Article
- Biofunctionalization of Magneto-Plasmonic FeMolecules (Basel, Switzerland) · 2025Article
- Recent advances in applications of artificial intelligence-assisted Raman spectroscopy in diagnosis of cancers.Frontiers in molecular biosciences · 2025Review
- Utilizing surface-enhanced Raman spectroscopy for the adjunctive diagnosis of osteoporosis.European journal of medical research · 2024Article
- Article
- Recent progress in Surface-Enhanced Raman Spectroscopy detection of biomarkers in liquid biopsy for breast cancer.Frontiers in oncology · 2024Review
- Label-free atherosclerosis diagnosis through a blood drop of apolipoprotein E knockout mouse model using surface-enhanced Raman spectroscopy validated by machine learning algorithm.Bioengineering & translational medicine · 2023Article
- High-Precision Detection of Cellular Drug Response Based on SERS Spectrum and Multivariate Statistical Analysis.Biosensors · 2023Article
- SERS-Based Biosensors Combined with Machine Learning for Medical Application.ChemistryOpen · 2023Review
- Machine learning using convolutional neural networks for SERS analysis of biomarkers in medical diagnostics.Journal of Raman spectroscopy : JRS · 2022Article
- Trends in Application of SERS Substrates beyond Ag and Au, and Their Role in Bioanalysis.Biosensors · 2022Review
- Article
- Rapid detection of hysteromyoma and cervical cancer based on serum surface-enhanced Raman spectroscopy and a support vector machine.Biomedical optics express · 2022Article
- Machine Learning-Assisted Sampling of Surfance-Enhanced Raman Scattering (SERS) Substrates Improve Data Collection Efficiency.Applied spectroscopy · 2022Article
- Comparison of Surface-Enhanced Raman Scattering Properties of Serum and Urine for the Detection of Chronic Kidney Disease in Patients.Applied spectroscopy · 2021Article
- Decoding Optical Data with Machine Learning.Laser & photonics reviews · 2021Article
- Modeling and comparing data mining algorithms for prediction of recurrence of breast cancer.PloS one · 2020Article
- Surface-enhanced Raman spectroscopy analysis of mast cell degranulation induced by low-intensity laser.IET nanobiotechnology · 2019Article
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In this paper, we investigated the feasibility of using surface enhanced Raman spectroscopy (SERS) and multivariate analysis method to discriminate liver cancer and nasopharyngeal cancer from healthy volunteers. SERS measurements were performed on serum protein samples from 104 liver cancer patients, 100 nasopharyngeal cancer patients, and 95 healthy volunteers. Two dimensionality reduction methods, principal component analysis (PCA) and partial least square (PLS) were compared, and the results indicated that the performance of PLS is superior to that of PCA. When the number of components was compressed to 3 by PLS, support vector machine (SVM) with a Gaussian radial basis function (RBF) was employed to classify various cancers simultaneously. Based on the PLS-SVM algorithm, high diagnostic accuracies of 95.09% and 90.67% were achieved from the training set and the unknown testing set, respectively. The results of this exploratory work demonstrate that serum protein SERS technology combined with PLS-SVM diagnostic algorithm has great potential for the noninvasive screening of cancer.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.