Yusuke Saeki
;
Naoki Maki
;
Takahiro Nemoto
(National Institute for Materials Science)
;
Katsushige Inada
;
Kosuke Minami
(National Institute for Materials Science)
;
Ryo Tamura
(National Institute for Materials Science)
;
Gaku Imamura
(National Institute for Materials Science)
;
Yukiko Cho-Isoda
;
Shinsuke Kitazawa
;
Hiroshi Kojima
;
Genki Yoshikawa
(National Institute for Materials Science)
;
Yukio Sato
説明:
(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.
権利情報:
キーワード: Lung cancer, Breath analysis, Electronic nose (e-nose), Membrane-type Surface stress Sensor (MSS), Machine learning
刊行年月日: 2024-02-25
出版者: Elsevier BV
掲載誌:
研究助成金:
原稿種別: 著者最終稿 (Accepted manuscript)
MDR DOI: https://doi.org/10.48505/nims.5227
公開URL: https://doi.org/10.1016/j.lungcan.2024.107514
関連資料:
その他の識別子:
連絡先:
更新時刻: 2025-02-25 12:30:08 +0900
MDRでの公開時刻: 2025-02-25 12:30:09 +0900
| ファイル名 | サイズ | |||
|---|---|---|---|---|
| ファイル名 |
Manuscript R1(clean).docx
(サムネイル)
application/vnd.openxmlformats-officedocument.wordprocessingml.document |
サイズ | 60.3KB | 詳細 |