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- W4220832849 abstract "Post surgery acute endophthalmitis is a rare ocular disease that is most prevalent among patients with cataract surgery. It is difficult to identify these rare but possible disease as the symptoms are not quite visible. In addition, endophthalmitis introduces significant burden in public health and requires patients to undergo increased physician visits and procedures such as pars plana vitrectomy. Eventually, endophthalmitis patients become impaired with reduced vision and degraded quality of life. Therefore, the early diagnosis or prediction of acute endophthalmitis would benefit a significant portion of the patients to lead healthy life after the cataract surgery. In this paper, we propose PrediCatE (Predicting Cataract surgery based acute Endophthalmitis), a prediction technique that is applied on patients' previous visits to predict acute endophthalmitis after their cataract surgery. We specifically apply neighborhood based language modeling and classification algorithms on the IRIS® Registry (Intelligent Research in Sight) dataset. Our empirical results demonstrate promising outcomes that will enhance the development and evaluation process of predictive modeling approaches in ophthalmic healthcare." @default.
- W4220832849 created "2022-04-03" @default.
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- W4220832849 date "2022-01-01" @default.
- W4220832849 modified "2023-09-23" @default.
- W4220832849 title "PrediCatE: Predicting Acute Endophthalmitis for Patients with Cataract Surgery" @default.
- W4220832849 doi "https://doi.org/10.1109/icsc52841.2022.00013" @default.
- W4220832849 hasPublicationYear "2022" @default.
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