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

doi:10.5662/wjm.v14.i2.92267

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World Journal of Methodology

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2222-0682

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

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

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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