Machine Learning Enhanced Optical Spectroscopy for Disease Detection

doi:10.1021/acs.jpclett.2c02193

	Machine Learning Enhanced Optical Spectroscopy for Disease Detection
	Lv, Ruichan 1; Wang, Zhan 1; Ma, Yaqun 1; Li, Wenjing 1; Tian, Jie 2
发表期刊	JOURNAL OF PHYSICAL CHEMISTRY LETTERS
ISSN	1948-7185
	2022-09-29
页码	12
通讯作者	Lv, Ruichan(rclv@xidian.edu.cn) ; Tian, Jie(jie.tian@ia.ac.cn)
摘要	Optical spectroscopy plays an important role in disease detection. Improving the sensitivity and specificity of spectral detection has great importance in the development of accurate diagnosis. The development of artificial intelligence technology provides a great opportunity to improve the detection accuracy through machine learning methods. In this Perspective, we focus on the combination of machine learning methods with the optical spectroscopy methods widely used for disease detection, including absorbance, fluorescence, scattering, FTIR, terahertz, etc. By comparing the spectral analysis with different machine learning methods, we illustrate that the support vector machine and convolutional neural network are most effective, which have potential to further improve the classification accuracy to distinguish disease subtypes if these machine learning methods are used. This Perspective broadens the scope of optical spectroscopy enhanced by machine learning and will be useful for the development of disease detection.
DOI	10.1021/acs.jpclett.2c02193
关键词[WOS]	RAMAN-SPECTROSCOPY ; BIOMEDICAL APPLICATIONS ; TERAHERTZ SPECTROSCOPY ; CANCER ; FTIR ; IDENTIFICATION ; DIAGNOSIS ; BLOOD ; MODEL ; RDX
收录类别	SCI
语种	英语
资助项目	National Key R & D Program of China ; National Scientific Foundation of China ; Fundamental Research Funds for the Central Universities ; [2017YFA0205202] ; [2018YFC0910602] ; [81801744]
项目资助者	National Key R & D Program of China ; National Scientific Foundation of China ; Fundamental Research Funds for the Central Universities
WOS研究方向	Chemistry ; Science & Technology - Other Topics ; Materials Science ; Physics
WOS类目	Chemistry, Physical ; Nanoscience & Nanotechnology ; Materials Science, Multidisciplinary ; Physics, Atomic, Molecular & Chemical
WOS记录号	WOS:000864556000001
出版者	AMER CHEMICAL SOC
引用统计	被引频次：4[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/50362
专题	中国科学院分子影像重点实验室
通讯作者	Lv, Ruichan; Tian, Jie
作者单位	1.Xidian Univ, Engn Res Ctr Mol & NeuroImaging, Minist Educ, Sch Life Sci & Technol,Interdisciplinary Res Ctr S, Xian 710071, Shaanxi, Peoples R China 2.Chinese Acad Sci, Inst Automat, Key Lab Mol Imaging, Beijing 100190, Peoples R China
通讯作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Lv, Ruichan,Wang, Zhan,Ma, Yaqun,et al. Machine Learning Enhanced Optical Spectroscopy for Disease Detection[J]. JOURNAL OF PHYSICAL CHEMISTRY LETTERS,2022:12.
APA	Lv, Ruichan,Wang, Zhan,Ma, Yaqun,Li, Wenjing,&Tian, Jie.(2022).Machine Learning Enhanced Optical Spectroscopy for Disease Detection.JOURNAL OF PHYSICAL CHEMISTRY LETTERS,12.
MLA	Lv, Ruichan,et al."Machine Learning Enhanced Optical Spectroscopy for Disease Detection".JOURNAL OF PHYSICAL CHEMISTRY LETTERS (2022):12.