Publication Name	World Journal of Radiology
Manuscript ID	25005
Country	Italy

Received	2016-02-18 08:52
Peer-Review Started	2016-02-21 19:47
To Make the First Decision	2016-03-23 11:38
Return for Revision	2016-03-25 16:54
Revised	2016-04-12 01:31
Second Decision	2016-05-27 13:54
Accepted by Journal Editor-in-Chief	2016-05-27 15:21
Accepted by Company Editor-in-Chief	2016-07-13 14:20
Articles in Press	2016-07-13 14:20
Publication Fee Transferred
Edit the Manuscript by Language Editor	2016-07-14 08:11
Typeset the Manuscript	2016-08-17 16:00
Publish the Manuscript Online	2016-08-26 08:31

ISSN	1949-8470 (online)
Open Access	This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (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) 2016. Published by Baishideng Publishing Group Inc. All rights reserved.
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Website	http://www.wjgnet.com

Category	Radiology, Nuclear Medicine & Medical Imaging
Manuscript Type	Diagnostic Advances
Article Title	Enhanced characterization of solid solitary pulmonary nodules with Bayesian analysis-based computer-aided diagnosis
Manuscript Source	Invited Manuscript
All Author List	Simone Perandini, Gian Alberto Soardi, Massimiliano Motton, Raffaele Augelli, Chiara Dallaserra, Gino Puntel, Arianna Rossi, Giuseppe Sala, Manuel Signorini, Laura Spezia, Federico Zamboni and Stefania Montemezzi
Funding Agency and Grant Number
Corresponding Author	Simone Perandini, MD, Department of Radiology, Azienda Ospedaliera Universitaria Integrata di Verona, Piazzale Stefani 1, 37100 Verona, Italy. simone.perandini@ospedaleuniverona.it
Key Words	Solitary pulmonary nodule; Computer-aided diagnosis; Lung neoplasms; Multidetector computed tomography; Bayesian prediction
Core Tip	The aim of this study was to prospectively assess the net accuracy gain of using computer-aided diagnosis in characterizing solitary pulmonary nodules detected at computed tomography. One-hundred randomly selected nodules with a definitive diagnosis were reviewed by 7 radiologists, before and after computer predictions. A net gain in diagnostic accuracy was found in 6 out of 7 readers. This study provides further evidence supporting the integration of computer aided diagnosis in nodule characterization.
Publish Date	2016-08-26 08:31
Citation	Perandini S, Soardi GA, Motton M, Augelli R, Dallaserra C, Puntel G, Rossi A, Sala G, Signorini M, Spezia L, Zamboni F, Montemezzi S. Enhanced characterization of solid solitary pulmonary nodules with Bayesian analysis-based computer-aided diagnosis. World J Radiol 2016; 8(8): 729-734
URL	http://www.wjgnet.com/1949-8470/full/v8/i8/729.htm
DOI	http://dx.doi.org/10.4329/wjr.v8.i8.729

Full Article (PDF)	WJR-8-729.pdf
Full Article (Word)	WJR-8-729.doc
Manuscript File	25005-Review.doc
Answering Reviewers	25005-Answering reviewers.pdf
Audio Core Tip	25005-Audio core tip.mp3
Conflict-of-Interest Disclosure Form	25005-Conflict-of-interest statement.pdf
Copyright License Agreement	25005-Copyright assignment.pdf
Peer-review Report	25005-Peer-review(s).pdf
Journal Editor-in-Chief Review Report	25005-Journal editor-in-chief review report.pdf
Scientific Misconduct Check	25005-Scientific misconduct check.pdf
Scientific Editor Work List	25005-Scientific editor work list.pdf