A Review of Surface-Enhanced Raman Spectroscopy on Potential Clinical Applications Towards Diagnosing Colorectal Cancer
Publish place: Multidisciplinary Cancer Investigation، Vol: 5، Issue: 1
Publish Year: 1399
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:
JR_MCIJO-5-1_003
تاریخ نمایه سازی: 15 بهمن 1399
Abstract:
Colorectal cancer (CRC) is one of the leading cancers in the world and early-screening is still the best method of cancer patient survival. However, colonoscopy as the current gold standard is not without flaws and an emerging technique called surface-enhanced Raman spectroscopy (SERS) coupled with machine learning is a possible candidate that could be applied in parallel with colonoscopy. This paper looks into the principles of SERS along with one of the most used machine learning algorithms: principal component analysis (PCA), and linear discriminate analysis (LDA). Case studies will be presented in the SERS application towards early screening, targeted imaging, and alternative diagnosis. The paper will conclude with the authors’ analysis of the current landscape of SERS implementation into clinical applications. This review article highlights the promising technology of SERS as a potentially useful tool for clinicians and calls their attention toward this emerging technology.
Keywords:
Colorectal Neoplasms , Spectrum Analysis , Raman , Molecular Imaging , Machine Learning , Algorithms , Early Detection of Cancer
Authors
Owen Liang
Department of Materials Science and Engineering, University of California, Los Angeles, Los Angeles, California, USA
Ya-Hong Xie
Department of Materials Science and Engineering, University of California, Los Angeles, Los Angeles, California, USA & Jonsson Comprehensive Cancer Center, University of California, Los Angeles, Los Angeles, California, USA
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