Machine Learning Enhanced Optical Spectroscopy for Disease Detection

doi:10.1021/acs.jpclett.2c02193

CORC > 自动化研究所 > 中国科学院自动化研究所 > 中国科学院分子影像重点实验室

	Machine Learning Enhanced Optical Spectroscopy for Disease Detection
	Lv, Ruichan 2; Wang, Zhan 2; Ma, Yaqun 2; Li, Wenjing 2; Tian, Jie 1
刊名	JOURNAL OF PHYSICAL CHEMISTRY LETTERS
	2022-09-29
页码	12
ISSN号	1948-7185
DOI	10.1021/acs.jpclett.2c02193
通讯作者	Lv, Ruichan(rclv@xidian.edu.cn) ; Tian, Jie(jie.tian@ia.ac.cn)
英文摘要	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.
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]
WOS关键词	RAMAN-SPECTROSCOPY ; BIOMEDICAL APPLICATIONS ; TERAHERTZ SPECTROSCOPY ; CANCER ; FTIR ; IDENTIFICATION ; DIAGNOSIS ; BLOOD ; MODEL ; RDX
WOS研究方向	Chemistry ; Science & Technology - Other Topics ; Materials Science ; Physics
语种	英语
出版者	AMER CHEMICAL SOC
WOS记录号	WOS:000864556000001
资助机构	National Key R & D Program of China ; National Scientific Foundation of China ; Fundamental Research Funds for the Central Universities
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/50361]
专题	自动化研究所_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.Chinese Acad Sci, Inst Automat, Key Lab Mol Imaging, Beijing 100190, Peoples R China 2.Xidian Univ, Engn Res Ctr Mol & NeuroImaging, Minist Educ, Sch Life Sci & Technol,Interdisciplinary Res Ctr S, Xian 710071, Shaanxi, Peoples R China
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.