Article Lung cancer detection in perioperative patients' exhaled breath with nanomechanical sensor array

Yusuke Saeki ; Naoki Maki ; Takahiro Nemoto (National Institute for Materials Science) ; Katsushige Inada ; Kosuke Minami SAMURAI ORCID (National Institute for Materials Science) ; Ryo Tamura SAMURAI ORCID (National Institute for Materials Science) ; Gaku Imamura SAMURAI ORCID (National Institute for Materials Science) ; Yukiko Cho-Isoda ; Shinsuke Kitazawa ; Hiroshi Kojima ; Genki Yoshikawa SAMURAI ORCID (National Institute for Materials Science) ; Yukio Sato

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Yusuke Saeki, Naoki Maki, Takahiro Nemoto, Katsushige Inada, Kosuke Minami, Ryo Tamura, Gaku Imamura, Yukiko Cho-Isoda, Shinsuke Kitazawa, Hiroshi Kojima, Genki Yoshikawa, Yukio Sato. Lung cancer detection in perioperative patients' exhaled breath with nanomechanical sensor array. Lung Cancer. 2024, 190 (), 107514. https://doi.org/10.1016/j.lungcan.2024.107514
SAMURAI

Description:

(abstract)

Breath analysis using a chemical sensor array combined with machine learning algorithms may be applicable for detecting and screening lung cancer. In this study, we examined whether perioperative breath analysis can predict the presence of lung cancer using a Membrane-type Surface stress Sensor (MSS) array and machine learning.

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Keyword: Lung cancer, Breath analysis, Electronic nose (e-nose), Membrane-type Surface stress Sensor (MSS), Machine learning

Date published: 2024-02-25

Publisher: Elsevier BV

Journal:

  • Lung Cancer (ISSN: 01695002) vol. 190 107514

Funding:

  • Government of Japan Ministry of Education Culture Sports Science and Technology
  • Japan Cabinet Office

Manuscript type: Author's version (Accepted manuscript)

MDR DOI: https://doi.org/10.48505/nims.5227

First published URL: https://doi.org/10.1016/j.lungcan.2024.107514

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Updated at: 2025-02-25 12:30:08 +0900

Published on MDR: 2025-02-25 12:30:09 +0900

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