Differentiating Choroidal Melanomas and Nevi Using a Self-Supervised Deep Learning Model Applied to Clinical Fundoscopy Images

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Authors

Institutions

Publication Details

Journal
Ophthalmology Science
Published
2024-11-08
DOI
https://doi.org/10.1016/j.xops.2024.100647
Citations
12
Primary Topic
Ocular Oncology and Treatments
Type
article
Field-Weighted Citation Impact
6.46

Funders

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article

Differentiating Choroidal Melanomas and Nevi Using a Self-Supervised Deep Learning Model Applied to Clinical Fundoscopy Images

Melanie Jackson, Rumana Hussain, Sarah E. Coupland, Helen Kalirai et al.
12 citations
Ophthalmology Science
Ocular Oncology and Treatments
6.46
article

Differentiating Choroidal Melanomas and Nevi Using a Self-Supervised Deep Learning Model Applied to Clinical Fundoscopy Images

Melanie Jackson, Rumana Hussain, Sarah E. Coupland, Helen Kalirai, Yalin Zheng, Heinrich Heimann
article en
12 citations

Abstract

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Ophthalmology ScienceVol. 5(2)
University of Liverpool (GB), Aintree University Hospitals NHS Foundation Trust (GB), Liverpool College (GB), Liverpool Heart and Chest Hospital (GB), Vision Eye Institute (AU), Liverpool John Moores University (GB)
National Institute for Health and Care Research, Department of Health and Social Care, North West Cancer Research
No poverty
Openalex Percentile: Top 3%
Ocular Oncology and Treatments
6.46
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Differentiating Choroidal Melanomas and Nevi Using a Self-Supervised Deep Learning Model Applied to Clinical Fundoscopy Images — Melanie Jackson, Rumana Hussain, et al. · Ophthalmology Science (2024) | TGRS Research Map | TGRS