Artificial Breath Classification Using XGBoost Algorithm for Diabetes Detection

Exhaled breath analysis has become more and more popular as a supplementary tool for medical diagnosis. However, the number of variables that have to be taken into account forces researchers to develop novel algorithms for proper data interpretation. This paper presents a system for analyzing exhaled air with the use of various sensors. Breath simulations with acetone as a diabetes biomarker were performed using the proposed e-nose system. The XGBoost algorithm for diabetes detection based on artificial breath analysis is presented. The results have shown that the designed system based on the XGBoost algorithm is highly selective for acetone, even at low concentrations. Moreover, in comparison with other commonly used algorithms, it was shown that XGBoost exhibits the highest performance and recall.

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Exhaled Breath Analysis to Predict Risk of Symptomatic Pneumonitis

Case Medical Research ◽

10.31525/ct1-nct04040244 ◽

2019 ◽

Author(s):

Keyword(s):

Breath Analysis ◽

Exhaled Breath ◽

Exhaled Breath Analysis

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A comparative study on the VOCs gas sensing properties of Zn2SnO4 nanoparticles, hollow cubes, and hollow octahedra towards exhaled breath analysis

Sensors and Actuators B Chemical ◽

10.1016/j.snb.2021.130147 ◽

2021 ◽

pp. 130147

Author(s):

Nguyen Hong Hanh ◽

Trinh Minh Ngoc ◽

Lai Van Duy ◽

Chu Manh Hung ◽

Nguyen Van Duy ◽

...

Keyword(s):

Comparative Study ◽

Gas Sensing ◽

Breath Analysis ◽

Exhaled Breath ◽

Sensing Properties ◽

Exhaled Breath Analysis ◽

Gas Sensing Properties

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Modular Breath Analyzer (MBA): Introduction of a Breath Analyzer Platform Based on an Innovative and Unique, Modular eNose Concept for Breath Diagnostics and Utilization of Calibration Transfer Methods in Breath Analysis Studies

Molecules ◽

10.3390/molecules26123776 ◽

2021 ◽

Vol 26 (12) ◽

pp. 3776

Author(s):

Carsten Jaeschke ◽

Marta Padilla ◽

Johannes Glöckler ◽

Inese Polaka ◽

Martins Leja ◽

...

Keyword(s):

Real Life ◽

Sensor Arrays ◽

Breath Analysis ◽

Exhaled Breath ◽

Calibration Transfer ◽

Early Disease Detection ◽

Exhaled Breath Analysis ◽

Breath Analyzer ◽

Analysis Experiment ◽

Before And After

Exhaled breath analysis for early disease detection may provide a convenient method for painless and non-invasive diagnosis. In this work, a novel, compact and easy-to-use breath analyzer platform with a modular sensing chamber and direct breath sampling unit is presented. The developed analyzer system comprises a compact, low volume, temperature-controlled sensing chamber in three modules that can host any type of resistive gas sensor arrays. Furthermore, in this study three modular breath analyzers are explicitly tested for reproducibility in a real-life breath analysis experiment with several calibration transfer (CT) techniques using transfer samples from the experiment. The experiment consists of classifying breath samples from 15 subjects before and after eating a specific meal using three instruments. We investigate the possibility to transfer calibration models across instruments using transfer samples from the experiment under study, since representative samples of human breath at some conditions are difficult to simulate in a laboratory. For example, exhaled breath from subjects suffering from a disease for which the biomarkers are mostly unknown. Results show that many transfer samples of all the classes under study (in our case meal/no meal) are needed, although some CT methods present reasonably good results with only one class.

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