Attenuated total reflection FTIR dataset for identification of type 2 diabetes using saliva

• Published in: Computational and structural biotechnology journal 2022-01, Vol.20, p.4542-4548
• Main Authors: Sanchez-Brito, Miguel, Vazquez-Zapien, Gustavo J., Luna-Rosas, Francisco J., Mendoza-Gonzalez, Ricardo, Martinez-Romo, Julio C., Mata-Miranda, Monica M.
• Format: Article
• Language: English
• Subjects: A1C Test; Attenuated total reflection FTIR; Data; Dataset; Diabetes; Glucose; Saliva
• ISSN: 2001-0370; 2001-0370
• DOI: 10.1016/j.csbj.2022.08.038

Diabetes is one of the top 5 non-communicable diseases that occur worldwide according to the World Health Organization. Despite not being a fatal disease, a late diagnosis as well as poor control can cause a fatal outcome, because of that, several studies have been carried out with the aim of proposing additional techniques to the gold standard to assist in the diagnosis and control of this disease in a non-invasive way. Considering the above, and in order to provide a solid starting point for future researches, we share a primary research dataset with 1040 saliva samples obtained by Fourier Transform Infrared Spectroscopy considering the Attenuated Total Reflectance method. Database include: gender, age, individuals (patients) with/without diabetes, the glucose value, and the result to the A1C test for the diabetic population. We believe that sharing dataset as is could increase experimentation, research, and analysis of spectra through different strategies broaden its range of applicability by chemists, doctors, physicists, computer scientists, among others, to identify the effects that the virus causes in the body and to propose possible clinical treatments as well as to develop devices that allow us to assist in the characterization of possible carriers.