Early Diagnosis of Type 2 Diabetes Based on Near-Infrared Spectroscopy Combined With Machine Learning and Aquaphotomics

Abstract

Early diagnosis is important to reduce the incidence and mortality rate of diabetes. The feasibility of early diagnosis of diabetes was studied via near-infrared spectra (NIRS) combined with a support vector machine (SVM) and aquaphotomics. Firstly, the NIRS of entire blood samples from the population of healthy, pre-diabetic, and diabetic patients were obtained. The spectral data of the entire spectra in the visible and near-infrared region (400–2,500 nm) were used as the research object of the qualitative analysis. Secondly, several preprocessing steps including multiple scattering correction, variable standardization, and first derivative and second derivative steps were performed and the best pretreatment method was selected. Finally, for the early diagnosis of diabetes, models were established using SVM. The first overtone of water (1,300–1,600 nm) was used as the research object for an aquaphotomics model, and the aquagram of the healthy group, pre-diabetes, and diabetes groups were drawn using 12 water absorption patterns for the early diagnosis of diabetes. The results of SVM showed that the highest accuracy was 97.22% and the specificity and sensitivity were 95.65 and 100%, respectively when the pretreatment method of the first derivative was used, and the best model parameters were c = 18.76 and g = 0.008583.The results of the aquaphotomics model showed clear differences in the 1,400–1,500 nm region, and the number of hydrogen bonds in water species (1,408, 1,416, 1,462, and 1,522 nm) was evidently correlated with the occurrence and development of diabetes. The number of hydrogen bonds was the smallest in the healthy group and the largest in the diabetes group. The suggested reason is that the water matrix of blood changes with the worsening of blood glucose metabolic dysfunction. The number of hydrogen bonds could be used as biomarkers for the early diagnosis of diabetes. The result show that it is effective and feasible to establish an accurate and rapid early diagnosis model of diabetes via NIRS combined with SVM and aquaphotomics.

A novel diagnostic approach to Paratuberculosis in dairy cattle using near-infrared spectroscopy and aquaphotomics

“…Early diagnosis of type 2 diabetes based on NIRS and SVM model with aquaphotomics approach showed 97.22% accuracy, and the specificity and sensitivity were 95.65% and 100%, respectively, by the first derivative pretreatment. This study demonstrates that combining NIRS with aquaphotomics is effective for developing an accurate and rapid early diabetes diagnosis model ( Li et al., 2020 ).…”

“…Aquaphotomics was applied for discrimination of healthy and mastitic animals based on the spectra of urine, blood, and milk of dairy cows ( Tsenkova and Atanassova, 2001 ; Tsenkova, 2007 ; Meilina et al., 2009 ; Morita et al., 2013 ), estrus detection in cow and panda ( Kinoshita et al., 2012a , 2015 ; Iweka et al., 2020 ), discrimination of different bacteria strains ( Remagni et al., 2013 ; Slavchev et al., 2015 , 2017 ; Kovacs et al., 2019 ), pneumonia in dairy calves ( Santos-Rivera et al., 2021 ), and detection of type2 diabetic ( Li et al., 2020 ).…”

Compact Instrumentation for Accurate Detection and Measurement of Glucose Concentration Using Photoacoustic Spectroscopy

“…In [5], the signal detection uses a wideband low-noise amplifier (LNA), which can be susceptible to noise, unlike the phase sensitive lock-in amplifier IC used in this paper. Very recently, multiple stochastic and machine learning techniques have been reported for NIR optical spectroscopy [17][18][19][20] but none of them was extended to the photoacoustic approach. The machine learning techniques reported in [17] mentions using complex algorithms such as Random Forest Regression, Extra Trees Regression, Support Vector Machine (SVM) Regression, etc.…”

“…Similarly, convolutional neural network (CNN) was used for NIR signal classification for different glucose concentration in the range of 50 -430mg/dl as reported in [18]. NIR spectroscopy was used in combination with SVM to study the changes in water absorption for the early diagnosis of diabetes [20]. When compared to these reported recent articles, ordinary linear least squares (LLS) regression technique has been successfully used in this paper to model the relationship between the glucose concentrations and the voltage outputs of the designed circuit.…”

Aquaphotomics monitoring of strawberry fruit during cold storage – A comparison of two cooling systems

“…This research aimed to utilize aquaphotomic NIRS for monitoring during cold storage and better understanding of the mechanisms for maintaining freshness, choosing the strawberry fruit as a fruit-model system. The combination of NIRS and aquaphotomics has been already used to monitor aqueous and biological systems non-invasively for various purposes, such as evaluation of fresh and processed fruits and vegetables quality (36)(37)(38)(39)(40)(41)(42), milk quality (43,44), viral infections in plants, bacterial cultures (45,46) and fermentation (47)(48)(49), and physiological monitoring and diagnostics in higher organisms (50)(51)(52)(53)(54)(55). The second aim of the investigation was to compare the effects of different cooling technologies on the preservation of strawberries.…”