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

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References

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  1. I. A. Bratchenko, D. N. Artemyev, J. A. Khristophorova, and L. A. Shamina, “Use of Raman spectroscopy to screen diabetes mellitus with machine learning tools”: comment,” Biomed. Opt. Express 10(9), 4489–4491 (2019).
    [Crossref]
  2. E. Guevara, J. C. Torres-Galván, M. G. Ramírez-Elías, C. Luevano-Contreras, and F. J. González, “Use of Raman spectroscopy to screen diabetes mellitus with machine learning tools,” Biomed. Opt. Express 9(10), 4998–5010 (2018).
    [Crossref]
  3. E. Guevara, J. C. Torres-Galván, M. G. Ramírez Elías, C. Luevano-Contreras, and F. J. González, “Raman spectroscopy of Diabetes,” https://kaggle.com/codina/raman-spectroscopy-of-diabetes .
  4. G.-B. Huang, “Learning capability and storage capacity of two-hidden-layer feedforward networks,” IEEE Trans. Neural Netw. 14(2), 274–281 (2003).
    [Crossref]

2019 (1)

2018 (1)

2003 (1)

G.-B. Huang, “Learning capability and storage capacity of two-hidden-layer feedforward networks,” IEEE Trans. Neural Netw. 14(2), 274–281 (2003).
[Crossref]

Artemyev, D. N.

Bratchenko, I. A.

González, F. J.

E. Guevara, J. C. Torres-Galván, M. G. Ramírez-Elías, C. Luevano-Contreras, and F. J. González, “Use of Raman spectroscopy to screen diabetes mellitus with machine learning tools,” Biomed. Opt. Express 9(10), 4998–5010 (2018).
[Crossref]

E. Guevara, J. C. Torres-Galván, M. G. Ramírez Elías, C. Luevano-Contreras, and F. J. González, “Raman spectroscopy of Diabetes,” https://kaggle.com/codina/raman-spectroscopy-of-diabetes .

Guevara, E.

E. Guevara, J. C. Torres-Galván, M. G. Ramírez-Elías, C. Luevano-Contreras, and F. J. González, “Use of Raman spectroscopy to screen diabetes mellitus with machine learning tools,” Biomed. Opt. Express 9(10), 4998–5010 (2018).
[Crossref]

E. Guevara, J. C. Torres-Galván, M. G. Ramírez Elías, C. Luevano-Contreras, and F. J. González, “Raman spectroscopy of Diabetes,” https://kaggle.com/codina/raman-spectroscopy-of-diabetes .

Huang, G.-B.

G.-B. Huang, “Learning capability and storage capacity of two-hidden-layer feedforward networks,” IEEE Trans. Neural Netw. 14(2), 274–281 (2003).
[Crossref]

Khristophorova, J. A.

Luevano-Contreras, C.

E. Guevara, J. C. Torres-Galván, M. G. Ramírez-Elías, C. Luevano-Contreras, and F. J. González, “Use of Raman spectroscopy to screen diabetes mellitus with machine learning tools,” Biomed. Opt. Express 9(10), 4998–5010 (2018).
[Crossref]

E. Guevara, J. C. Torres-Galván, M. G. Ramírez Elías, C. Luevano-Contreras, and F. J. González, “Raman spectroscopy of Diabetes,” https://kaggle.com/codina/raman-spectroscopy-of-diabetes .

Ramírez Elías, M. G.

E. Guevara, J. C. Torres-Galván, M. G. Ramírez Elías, C. Luevano-Contreras, and F. J. González, “Raman spectroscopy of Diabetes,” https://kaggle.com/codina/raman-spectroscopy-of-diabetes .

Ramírez-Elías, M. G.

Shamina, L. A.

Torres-Galván, J. C.

E. Guevara, J. C. Torres-Galván, M. G. Ramírez-Elías, C. Luevano-Contreras, and F. J. González, “Use of Raman spectroscopy to screen diabetes mellitus with machine learning tools,” Biomed. Opt. Express 9(10), 4998–5010 (2018).
[Crossref]

E. Guevara, J. C. Torres-Galván, M. G. Ramírez Elías, C. Luevano-Contreras, and F. J. González, “Raman spectroscopy of Diabetes,” https://kaggle.com/codina/raman-spectroscopy-of-diabetes .

Biomed. Opt. Express (2)

IEEE Trans. Neural Netw. (1)

G.-B. Huang, “Learning capability and storage capacity of two-hidden-layer feedforward networks,” IEEE Trans. Neural Netw. 14(2), 274–281 (2003).
[Crossref]

Other (1)

E. Guevara, J. C. Torres-Galván, M. G. Ramírez Elías, C. Luevano-Contreras, and F. J. González, “Raman spectroscopy of Diabetes,” https://kaggle.com/codina/raman-spectroscopy-of-diabetes .

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Figures (2)

Fig. 1.
Fig. 1. Raman spectra of AGEs and PC loadings of diabetic patients from data acquired at the cubital vein.
Fig. 2.
Fig. 2. Accuracy of the proposed ANN for different number of neurons.

Tables (1)

Tables Icon

Table 1. Comparison between classifiers