| dc.contributor.author |
Raman, Sundaresan |
|
| dc.date.accessioned |
2024-11-11T09:49:42Z |
|
| dc.date.available |
2024-11-11T09:49:42Z |
|
| dc.date.issued |
2022-09 |
|
| dc.identifier.uri |
https://journals.lww.com/ijo/fulltext/2022/09000/Advances_in_the_diagnosis_of_herpes_simplex.24.aspx?context=LatestArticles |
|
| dc.identifier.uri |
http://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/16323 |
|
| dc.description.abstract |
Infectious keratitis, especially viral keratitis (VK), in resource-limited settings, can be a challenge to diagnose and carries a high risk of misdiagnosis contributing to significant ocular morbidity. We aimed to employ and study the application of artificial intelligence-based deep learning (DL) algorithms to diagnose VK. |
en_US |
| dc.language.iso |
en |
en_US |
| dc.publisher |
Wolters Kluwer |
en_US |
| dc.subject |
Computer Science |
en_US |
| dc.subject |
Deep Learning (DL) |
en_US |
| dc.subject |
Necrotising keratitis |
en_US |
| dc.title |
Advances in the diagnosis of herpes simplex stromal necrotising keratitis: A feasibility study on deep learning approach |
en_US |
| dc.type |
Article |
en_US |