Recognizing lung cancer and stages using a self-developed electronic nose system

2021 ◽  
Vol 131 ◽  
pp. 104294
Author(s):  
Ke Chen ◽  
Lei Liu ◽  
Bo Nie ◽  
Binchun Lu ◽  
Lidan Fu ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Electronic Nose ◽  
Electronic Nose System

scholarly journals Detection of Lung Cancer and EGFR Mutation by Electronic Nose System

2017 ◽  
Vol 12 (10) ◽  
pp. 1544-1551 ◽  
Author(s):  
Dekel Shlomi ◽  
Manal Abud ◽  
Ori Liran ◽  
Jair Bar ◽  
Naomi Gai-Mor ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Electronic Nose ◽  
Egfr Mutation ◽  
Electronic Nose System

Electronic Nose Applications

2018 ◽  
pp. 104-131
Author(s):  
Ping Wang ◽  
Fan Gao ◽  
Xusheng Zhang ◽  
Min Wang
Keyword(s):  
Lung Cancer ◽  
Electronic Nose ◽  
Electrochemical Sensors ◽  
Bacterial Overgrowth ◽  
Lung Cancer Screening ◽  
Gastrointestinal Diseases ◽  
Small Intestinal Bacterial Overgrowth ◽  
Oxide Semiconductor ◽  
Diagnosis Of Lung Cancer ◽  
Electronic Nose System

In this chapter, the authors introduce three typical applications of electronic nose, including the diagnosis of lung cancer and gastrointestinal diseases and food freshness detection. Firstly, an electronic nose system intended for lung cancer screening employs semiconductor and electrochemical sensors to compose an array in a chamber to conduct breath analysis with pre-concentration and multiple desorption procedures. Secondly, a design of virtual electronic nose was presented to detect the concentration of hydrogen, methane, and carbon dioxide in breath for the diagnosis of small intestinal bacterial overgrowth. Finally, combined with the metal oxide semiconductor sensors and electrochemical sensors array, the small size electronic nose system is to identify the freshness and classify different kinds of food stored in the refrigerator.

scholarly journals MA01.01 Detection of Lung Cancer and EGFR Mutations by Electronic Nose System

2017 ◽  
Vol 12 (1) ◽  
pp. S342 ◽  
Author(s):  
Dekel Shlomi ◽  
Manal Abud-Hawa ◽  
Ori Liran ◽  
Jair Bar ◽  
Naomi Gai Mor ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Electronic Nose ◽  
Egfr Mutations ◽  
Electronic Nose System

scholarly journals Non-Invasive Method to Detect Infection with Mycobacterium tuberculosis Complex in Wild Boar by Measurement of Volatile Organic Compounds Obtained from Feces with an Electronic Nose System

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 584
Author(s):  
Kelvin de Jesús Beleño-Sáenz ◽  
Juan Martín Cáceres-Tarazona ◽  
Pauline Nol ◽  
Aylen Lisset Jaimes-Mogollón ◽  
Oscar Eduardo Gualdrón-Guerrero ◽  
...  
Keyword(s):  
Volatile Organic Compounds ◽  
Wild Boar ◽  
Organic Compounds ◽  
Electronic Nose ◽  
Bovine Tuberculosis ◽  
Human Beings ◽  
Non Invasive ◽  
Testing Phase ◽  
Volatile Organic ◽  
Electronic Nose System

More effective methods to detect bovine tuberculosis, caused by Mycobacterium bovis, in wildlife, is of paramount importance for preventing disease spread to other wild animals, livestock, and human beings. In this study, we analyzed the volatile organic compounds emitted by fecal samples collected from free-ranging wild boar captured in Doñana National Park, Spain, with an electronic nose system based on organically-functionalized gold nanoparticles. The animals were separated by the age group for performing the analysis. Adult (>24 months) and sub-adult (12–24 months) animals were anesthetized before sample collection, whereas the juvenile (<12 months) animals were manually restrained while collecting the sample. Good accuracy was obtained for the adult and sub-adult classification models: 100% during the training phase and 88.9% during the testing phase for the adult animals, and 100% during both the training and testing phase for the sub-adult animals, respectively. The results obtained could be important for the further development of a non-invasive and less expensive detection method of bovine tuberculosis in wildlife populations.

Lung Cancer Identification by an Electronic Nose based on an Array of MOS Sensors

2007 ◽  
Author(s):  
Rossella Blatt ◽  
Andrea Bonarini ◽  
Elisa Calabro ◽  
Matteo Della Torre ◽  
Matteo Matteucci ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Electronic Nose

scholarly journals Discrimination between Alternative Herbal Medicines from Different Categories with the Electronic Nose

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2936 ◽  
Author(s):  
Xianghao Zhan ◽  
Xiaoqing Guan ◽  
Rumeng Wu ◽  
Zhan Wang ◽  
You Wang ◽  
...  
Keyword(s):  
Herbal Medicine ◽  
Electronic Nose ◽  
Nearest Neighbor ◽  
Herbal Medicines ◽  
Principal Component ◽  
Support Vector ◽  
Linear Discriminant ◽  
Convenient Means ◽  
Electronic Nose System ◽  
Insight Into

As alternative herbal medicine gains soar in popularity around the world, it is necessary to apply a fast and convenient means for classifying and evaluating herbal medicines. In this work, an electronic nose system with seven classification algorithms is used to discriminate between 12 categories of herbal medicines. The results show that these herbal medicines can be successfully classified, with support vector machine (SVM) and linear discriminant analysis (LDA) outperforming other algorithms in terms of accuracy. When principal component analysis (PCA) is used to lower the number of dimensions, the time cost for classification can be reduced while the data is visualized. Afterwards, conformal predictions based on 1NN (1-Nearest Neighbor) and 3NN (3-Nearest Neighbor) (CP-1NN and CP-3NN) are introduced. CP-1NN and CP-3NN provide additional, yet significant and reliable, information by giving the confidence and credibility associated with each prediction without sacrificing of accuracy. This research provides insight into the construction of a herbal medicine flavor library and gives methods and reference for future works.

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