Non-invasive in vivo Raman spectroscopy of the skin for diabetes screening

被引：0

作者：

Guevara, Edgar ^{[1
,2
]}

Carlos Torres-Galvan, Juan ^{[2
]}

Ramirez Elias, Miguel G. ^{[3
]}

Luevano-Contreras, Claudia ^{[4
]}

Javier Gonzalez, Francisco ^{[2
]}

机构：

[1] CONACYT, Mexico City, DF, Mexico

[2] Univ Autonoma San Luis Potosi, Coordinat Innovat & Applicat Sci & Technol, San Luis Potosi, San Luis Potosi, Mexico

[3] Univ Autonoma San Luis Potosi, Fac Ciencias, San Luis Potosi, San Luis Potosi, Mexico

[4] Univ Guanajuato, Dept Med Sci, Guanajuato, Mexico

来源：

2017 PHOTONICS NORTH (PN) | 2017年

关键词：

Raman spectroscopy; diabetes; machine learning;

D O I：

暂无

中图分类号：

TB3 [工程材料学];

学科分类号：

0805 ; 080502 ;

摘要：

This work describes the application of portable Raman spectroscopy coupled with Artificial Neural Networks (ANN), to discern between diabetic patients and healthy controls, with a high degree of accuracy (Acc=89.7 +/- 6.6%). This technique is relatively low-cost, simple and comfortable for the patient, yielding rapid diagnosis. These features make our method a promising screening tool for identifying type 2 diabetes mellitus (DM2) in a non-invasive and automated fashion.

引用

页数：1

共 4 条

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[3] World Health Organization, 2016, World health organization
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Zhao, Jianhua
Lui, Harvey
McLean, David I.
Zeng, Haishan
[J]. APPLIED SPECTROSCOPY, 2007, 61 (11) : 1225 - 1232

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