Development of a breath detection method based E-nose system for lung cancer identification

Wong, De-Ming; Fang, Chen-Yu; Chen, Liying; Chiu, Chen-I; Chou, Ting-I; Wu, Cheng-Chun; Chiu, Shih-Wen; Tang, Kea-Tiong

doi:10.1109/icasi.2018.8394477

Cited by 9 publications

(2 citation statements)

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“…153 Another intriguing study combined seven multiplex gas sensors with a camera system to identify the various ripening stages of bananas after applying different methods of machine learning such as SVM, PCA, KNN, and LDA to analyze the obtained data from the samples. 154 Wong et al 155 developed a multiplex sensor array combined with PCA and LDA techniques to analyze the detection of lung cancer merely from the breath of a human being. To examine the data distribution, the combined system reduces the raw data to 2D with an accuracy of 84.4%.…”

Section: ■ Functional Materials For Sensingmentioning

confidence: 99%

Multiplexed Gas Sensor: Fabrication Strategies, Recent Progress, and Challenges

Verma,

Gokarna,

Kadiri

et al. 2023

ACS Sens.

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Due to miscellaneous toxic gases in the vicinity, there is a burgeoning need for advancement in the existing gas sensing technology not only for the survival of mankind but also for the industries based in various fields such as beverage, forestry, health care, environmental monitoring, agriculture, and military security. A gas sensor must be highly selective toward a specific gas in order to avoid incorrect signals while responding to nontarget gases. This may lead to complex scenarios depicting sensor defects, such as low selectivity and crosssensitivity. Therefore, a multiplex gas sensor is required to address the problems of cross selectivity by combining different gas sensors, signal processing, and pattern recognition techniques along with the currently employed gas sensing technologies. The different sensing materials used in these sensor arrays will produce a unique response signal for developing a set of identifiers as the input that can be used to recognize a specific gas by its "fingerprint". This review provides a comprehensive review of chemiresistive-based multiplex gas sensors, including various fabrication strategies from expensive to lowcost techniques, advances in sensing materials, and a gist of various pattern recognition techniques used for both rigid and flexible gas sensor applications. Finally, the review assesses the current state-of-the-art in multiplex gas sensor technology and discusses various challenges for future research in this direction.

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Section: ■ Functional Materials For Sensingmentioning

confidence: 99%

Multiplexed Gas Sensor: Fabrication Strategies, Recent Progress, and Challenges

Verma,

Gokarna,

Kadiri

et al. 2023

ACS Sens.

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“…As a result, the breath detection system was developed with the intention of assisting medical professionals in more rapidly screening for fast screening lung cancer. In the analysis, KNN and SVM are used, together with leave-one-out cross validation [11].…”

Section: Reviews On Lung Image Classification Systemsmentioning

confidence: 99%

CT Lung Image Classification Systems - A Systematic Review

Prabhakar¹,

Sivasubramanian²,

Sundaram³

et al. 2023

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Computer Aided Detection (CAD) and diagnostic technologies and their application have emerged in the last decade. CAD applications have concentrated on identification of the region of interest, for example nodules in the lung in the images, and analysis of the characteristics of objects. CAD technologies take advantages of computer systems as well as image processing and analysis techniques to overcome perceptual and interpretive errors caused by radiologists in the process of image observation and interpretation. This fact is inevitable in the context of medical practice since experience of image readers may vary and each observer (such as a radiologist) has a unique visual search on an image. Furthermore, there are always inter and intra observer variability for interpretation of an image. To overcome these difficulties, different CAD systems are developed for medical image analysis. This paper presents a systematic review on different CAD systems for lung cancer classification using computed tomography images.

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