Literature DB >> 31565505

Use of Raman spectroscopy to screen diabetes mellitus with machine learning tools: reply to comment.

Edgar Guevara1,2, Juan Carlos Torres-Galván2, Miguel G Ramírez-Elías3, Claudia Luevano-Contreras4, Francisco Javier González2.   

Abstract

We show the spectra of advanced glycation products in response to recent comments made by Bratchenko et al. Our results suggest that information retrieved by Raman spectroscopy is relevant to screening diabetic patients, however, the comparison carried out in our paper, between ANN and SVM, was not fair, because of the erroneous PCA selection procedure and different sources of variation present in the analysis.
© 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement.

Entities:  

Year:  2019        PMID: 31565505      PMCID: PMC6757467          DOI: 10.1364/BOE.10.004492

Source DB:  PubMed          Journal:  Biomed Opt Express        ISSN: 2156-7085            Impact factor:   3.732


  2 in total

1.  Learning capability and storage capacity of two-hidden-layer feedforward networks.

Authors:  Guang-Bin Huang
Journal:  IEEE Trans Neural Netw       Date:  2003

2.  Use of Raman spectroscopy to screen diabetes mellitus with machine learning tools.

Authors:  Edgar Guevara; Juan Carlos Torres-Galván; Miguel G Ramírez-Elías; Claudia Luevano-Contreras; Francisco Javier González
Journal:  Biomed Opt Express       Date:  2018-09-26       Impact factor: 3.732

  2 in total

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