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11/12/2020 3:59:23 AM | Browse: 428 | Download: 844
Publication Name World Journal of Gastrointestinal Oncology
Manuscript ID 58633
Country/Territory Japan
2020-07-31 07:16
Peer-Review Started
2020-07-30 11:56
To Make the First Decision
Return for Revision
2020-09-17 17:01
2020-09-28 14:24
Second Decision
2020-10-16 11:13
Accepted by Journal Editor-in-Chief
Accepted by Company Editor-in-Chief
2020-10-19 20:18
Articles in Press
2020-10-19 20:18
Publication Fee Transferred
Edit the Manuscript by Language Editor
2020-10-25 02:46
Typeset the Manuscript
2020-11-06 09:45
Publish the Manuscript Online
2020-11-12 03:59
ISSN 1948-5204 (online)
Open Access This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/Licenses/by-nc/4.0/
Copyright © The Author(s) 2020. Published by Baishideng Publishing Group Inc. All rights reserved.
Article Reprints For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
Permissions For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
Publisher Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
Website http://www.wjgnet.com
Category Gastroenterology and Hepatology
Manuscript Type Retrospective Study
Article Title Highly accurate colorectal cancer prediction model based on Raman spectroscopy using patient serum
Manuscript Source Invited Manuscript
All Author List Hiroaki Ito, Naoyuki Uragami, Tomokazu Miyazaki, William Yang, Kenji Issha, Kai Matsuo, Satoshi Kimura, Yuji Arai, Hiromasa Tokunaga, Saiko Okada, Machiko Kawamura, Noboru Yokoyama, Miki Kushima, Haruhiro Inoue, Takashi Fukagai and Yumi Kamijo
Author(s) ORCID Number
Hiroaki Ito http://orcid.org/0000-0002-0761-0632
Naoyuki Uragami http://orcid.org/0000-0003-2974-8250
Tomokazu Miyazaki http://orcid.org/0000-0002-6108-8945
William Yang http://orcid.org/0000-0002-8476-3026
Kenji Issha http://orcid.org/0000-0002-0782-6871
Kai Matsuo http://orcid.org/0000-0001-7951-2444
Satoshi Kimura http://orcid.org/0000-0002-6843-8127
Yuji Arai http://orcid.org/0000-0002-7776-715X
Hiromasa Tokunaga http://orcid.org/0000-0002-5842-9630
Saiko Okada http://orcid.org/0000-0003-1814-6449
Machiko Kawamura http://orcid.org/0000-0002-6138-1690
Noboru Yokoyama http://orcid.org/0000-0003-1882-0018
Miki Kushima http://orcid.org/0000-0002-1642-0478
Haruhiro Inoue http://orcid.org/0000-0002-0551-7274
Takashi Fukagai http://orcid.org/0000-0003-0261-6303
Yumi Kamijo http://orcid.org/0000-0002-4562-6926
Funding Agency and Grant Number
Funding Agency Grant Number
Japanese Society for the Promotion of Science (JSPS), based on the JSPS KAKENHI Grants-in-Aid for Scientific Research (C) JP17K09022
Corresponding Author Hiroaki Ito, MD, PhD, Associate Professor, Department of Surgery, Digestive Disease Center, Showa University Koto Toyosu Hospital, 5-1-38 Toyosu, Koto-ku, Tokyo 135-8577, Japan. h.ito@med.showa-u.ac.jp
Key Words Colorectal cancer; Raman spectroscopy; Machine learning; Blood; Serum; Diagnosis
Core Tip We developed a comprehensive, spontaneous, minimally invasive, label-free, blood-based colorectal cancer screening technique based on Raman spectroscopy. We used Raman spectra recorded using 184 serum samples obtained from patients undergoing colonoscopies. Use of the recorded Raman spectra as training data allowed the construction of a boosted tree colorectal cancer prediction model based on machine learning. The generalized R2 values for colorectal cancer was 0.9982. For machine learning using Raman spectral data, we are currently working on the construction of a more accurate colorectal cancer prediction model with a vast volume of additional data.
Publish Date 2020-11-12 03:59
Citation Ito H, Uragami N, Miyazaki T, Yang W, Issha K, Matsuo K, Kimura S, Arai Y, Tokunaga H, Okada S, Kawamura M, Yokoyama N, Kushima M, Inoue H, Fukagai T, Kamijo Y. Highly accurate colorectal cancer prediction model based on Raman spectroscopy using patient serum. World J Gastrointest Oncol 2020; 12(11): 1311-1324
URL https://www.wjgnet.com/1948-5204/full/v12/i11/1311.htm
DOI https://dx.doi.org/10.4251/wjgo.v12.i11.1311
Full Article (PDF) WJGO-12-1311.pdf
Full Article (Word) WJGO-12-1311.docx
Manuscript File 58633-Review-Filipodia.docx
Answering Reviewers 58633-Answering reviewers.pdf
Audio Core Tip 58633-Audio core tip.mp3
Biostatistics Review Certificate 58633-Biostatistics statement.PDF
Conflict-of-Interest Disclosure Form 58633-Conflict-of-interest statement.pdf
Copyright License Agreement 58633-Copyright license agreement.pdf
Approved Grant Application Form(s) or Funding Agency Copy of any Approval Document(s) 58633-Grant application form(s).pdf
Signed Informed Consent Form(s) or Document(s) 58633-Informed consent statement.pdf
Institutional Review Board Approval Form or Document 58633-Institutional review board statement.pdf
Non-Native Speakers of English Editing Certificate 58633-Language certificate.pdf
Supplementary Material 58633-Supplementary material.pdf
Peer-review Report 58633-Peer-review(s).pdf
Scientific Misconduct Check 58633-Bing-Ma YJ-1.jpg
Scientific Misconduct Check 58633-Bing-Chen XF-2.png
Scientific Misconduct Check 58633-Scientific misconduct check.pdf
Scientific Editor Work List 58633-Scientific editor work list.pdf