Novel automated non-invasive detection of ocular surface squamous neoplasia using artificial intelligence

doi:10.5662/wjm.v14.i2.92267

Advanced Search

BPG is committed to discovery and dissemination of knowledge

Home / Archive / Volume 14, Issue 2

This Article

Academic Content and Language Evaluation of This Article

CrossCheck and Google Search of This Article

Academic Rules and Norms of This Article

Citation of this article

Corresponding Author of This Article

Research Domain of This Article

Article-Type of This Article

Open-Access Policy of This Article

Times Cited Counts in Google of This Article

Number of Hits and Downloads for This Article

Total Article Views (211)

All Articles published online

The chart showing PDF series, HTML series, Figures (1-1) series, Tables (1-4) series.

Item

Count

PDF

HTML

160

Figures (1-1)

Tables (1-4)

Sum=199

Publishing Process of This Article

The chart showing Browse series, Download series.

Item

Count

Browse

Download

Sum=6

Jun 20, 2024 (publication date) through Jun 29, 2024

Times Cited of This Article

Times Cited (0)

Journal Information of This Article

Publication Name

World Journal of Methodology

ISSN

2222-0682

Publisher of This Article

Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

Minireviews

World J Methodol. Jun 20, 2024; 14(2): 92267
Published online Jun 20, 2024. doi: 10.5662/wjm.v14.i2.92267

Novel automated non-invasive detection of ocular surface squamous neoplasia using artificial intelligence

Sony Sinha, Prasanna Venkatesh Ramesh, Prateek Nishant, Arvind Kumar Morya, Ripunjay Prasad

Sony Sinha, Department of Ophthalmology–Vitreo Retina, Neuro Ophthalmology and Oculoplasty, All India Institute of Medical Sciences, Patna 801507, India

Prasanna Venkatesh Ramesh, Department of Glaucoma and Research, Mahathma Eye Hospital Private Limited, Trichy 620017, India

Prateek Nishant, Department of Ophthalmology, ESIC Medical College, Patna 801113, India

Arvind Kumar Morya, Department of Ophthalmology, All India Institute of Medical Sciences, Hyderabad 508126, India

Ripunjay Prasad, Department of Ophthalmology, RP Eye Institute, Delhi 110001, India

Author contributions: Sinha S, Ramesh PV and Nishant P analyzed data and wrote the manuscript; Sinha S and Nishant P performed research; Nishant P and Prasad R revised the manuscript; Morya AK designed the research.

Conflict-of-interest statement: The authors declare there are no conflicts of interest.

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/

Corresponding author: Arvind Kumar Morya, MBBS, MNAMS, Additional Professor, Department of Ophthalmology, All India Institute of Medical Sciences, Bibi Nagar, Hyderabad 508126, India. bulbul.morya@gmail.com

Received: January 20, 2024
Revised: February 19, 2024
Accepted: April 12, 2024
Published online: June 20, 2024
Processing time: 145 Days and 17.6 Hours

Core Tip

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 AI algorithms based on digital and histopathological images of OSSN.