Publication Name	World Journal of Methodology
Manuscript ID	92267
Country	India

Received	2024-01-20 15:34
Peer-Review Started	2024-01-20 15:34
To Make the First Decision
Return for Revision	2024-02-06 10:08
Revised	2024-02-19 08:09
Second Decision	2024-04-12 02:33
Accepted by Journal Editor-in-Chief
Accepted by Executive Editor-in-Chief	2024-04-12 08:04
Articles in Press	2024-04-12 08:04
Publication Fee Transferred
Edit the Manuscript by Language Editor	2024-04-19 03:34
Typeset the Manuscript	2024-05-27 07:25
Publish the Manuscript Online	2024-06-14 09:10

ISSN	2222-0682 (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: https://creativecommons.org/Licenses/by-nc/4.0/
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Category	Ophthalmology
Manuscript Type	Minireviews
Article Title	Novel automated non-invasive detection of ocular surface squamous neoplasia using artificial intelligence
Manuscript Source	Invited Manuscript
All Author List	Sony Sinha, Prasanna Venkatesh Ramesh, Prateek Nishant, Arvind Kumar Morya and Ripunjay Prasad
ORCID	Author(s) ORCID Number Sony Sinha http://orcid.org/0000-0002-6133-5977 Prasanna Venkatesh Ramesh http://orcid.org/0000-0002-6105-8666 Prateek Nishant http://orcid.org/0000-0003-3438-0040 Arvind Kumar Morya http://orcid.org/0000-0003-0462-119X
Funding Agency and Grant Number
Corresponding Author	Arvind Kumar Morya, MBBS, MNAMS, Additional Professor, Teacher, Department of Ophthalmology, All India Institute of Medical Sciences, Bibi Nagar , Hyderabad 508126, Telangana, India. bulbul.morya@gmail.com
Key Words	Conjunctival neoplasm; Early detection of cancer; Machine learning; Deep neural network; Precision medicine
Core Tip	This is a unique comprehensive review written on a common eye tumour-ocular surface squamous neoplasia (OSSN) and the role of artificial intelligence (AI) in the early diagnosis and management of this ocular condition. This write-up also covers the various intricacies involved in developing the AI algorithms based on digital and histopathological images of OSSN.
Publish Date	2024-06-14 09:10
Citation	<p>Sinha S, Ramesh PV, Nishant P, Morya AK, Prasad R. Novel automated non-invasive detection of ocular surface squamous neoplasia using artificial intelligence. <i>World J Methodol</i> 2024; 14(2): 92267</p>
URL	https://www.wjgnet.com/2222-0682/full/v14/i2/92267.htm
DOI	https://dx.doi.org/10.5662/wjm.v14.i2.92267

Full Article (PDF)	WJM-14-92267-with-cover.pdf
Manuscript File	92267-Review-Filipodia.docx
Answering Reviewers	92267-answering-reviewers.pdf
Audio Core Tip	92267-audio.mp3
Conflict-of-Interest Disclosure Form	92267-conflict-of-interest-statement.pdf
Copyright License Agreement	92267-copyright-assignment.pdf
Non-Native Speakers of English Editing Certificate	92267-non-native-speakers.pdf
Peer-review Report	92267-peer-reviews.pdf
Scientific Misconduct Check	92267-scientific-misconduct-check.png
Scientific Editor Work List	92267-scientific-editor-work-list.pdf
CrossCheck Report	92267-crosscheck-report.pdf