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

Open in New Tab Full Size Figure Download Figure

Figure 1 Typical features of ocular surface squamous neoplasia that can be recognized by artificial intelligence. A: Microphotograph showing normal squamous epithelium in the upper part along with dysplasia involving lower two-thirds of the epithelium and Invasive squamous cell carcinoma; B: Microphotograph in high magnification showing malignant squamous epithelial cells deep in the stroma arranged in an irregular island.

Citation: Sinha S, Ramesh PV, Nishant P, Morya AK, Prasad R. Novel automated non-invasive detection of ocular surface squamous neoplasia using artificial intelligence. World J Methodol 2024; 14(2): 92267
URL: https://www.wjgnet.com/2222-0682/full/v14/i2/92267.htm
DOI: https://dx.doi.org/10.5662/wjm.v14.i2.92267