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The dataset of our work where the application of portable Raman spectroscopy coupled with several supervised machine-learning techniques, is used to discern between diabetic patients (DM2) and healthy controls (Ctrl), with a high degree of accuracy. This script pre-processes the spectra to reproduce Fig. 1 of our paper: Use of Raman Spectroscopy to Screen Diabetes Mellitus with Machine Learning Tools Edgar Guevara, Juan Carlos Torres-Galván, Miguel G. Ramírez-Elías, Claudia Luevano-Contreras and Francisco Javier González Biomedical Optics Express (2018) _______________________________________________________________________________ Copyright (C) 2018 Edgar Guevara, PhD CONACYT-Universidad Autónoma de San Luis Potosí Coordinación para la Innovación y Aplicación de la Ciencia y la Tecnología _______________________________________________________________________________
The dataset of our work where the application of portable Raman spectroscopy coupled with several supervised machine-learning techniques, is used to discern between diabetic patients (DM2) and healthy controls (Ctrl), with a high degree of accuracy.
Download dataset from: https://www.kaggle.com/codina/raman-spectroscopy-of-diabetes
This script pre-processes the spectra to reproduce Fig. 1 of our paper:
Guevara, E., Torres-Galván, J. C., Ramírez-Elías, M. G., Luevano-Contreras, C., & González, F. J. (2018). Use of Raman spectroscopy to screen diabetes mellitus with machine learning tools. Biomedical Optics Express, 9(10), 4998–5010. https://doi.org/10.1364/BOE.9.004998
Copyright (C) 2018 Edgar Guevara, PhD CONACYT-Universidad Autónoma de San Luis Potosí Coordinación para la Innovación y Aplicación de la Ciencia y la Tecnología