Lee Ju-Yeun

🇪🇱 Seoul National University

3 articles in GJC

Using Machine Learning to Identify Ophthalmology Subspecialty Care and Advance Workforce Research with the IRIS® Registry (Intelligent Research in Sight).

Jeon Ju Hyun, Lee Ju-Yeun, Elze Tobias, Miller Joan W, Lorch Alice C, Ong Mei-Sing et al.

Ophthalmol SciJun 20250 citationsCross-Sectional Study

Machine learning models accurately identified ophthalmology subspecialists from IRIS Registry data, especially using procedure codes. This can help understand ophthalmic workforce trends and inform eye care policy.

Full abstract PubMed

Diagnostic value of ganglion cell-inner plexiform layer for early detection of ethambutol-induced optic neuropathy.

Lee Ju-Yeun, Han Jinu, Seo Jeong Gi, Park Kyung-Ah, Oh Sei Yeul

Br J OphthalmolApr 201815 citationsObservational Study

Macular GCIPL thickness, particularly minimum GCIPL, outperforms pRNFL for early detection of ethambutol-induced optic neuropathy, offering a superior diagnostic tool for this challenging condition.

Full abstract PubMed

Ganglion Cell Layer and Inner Plexiform Layer as Predictors of Vision Recovery in Ethambutol-Induced Optic Neuropathy: A Longitudinal OCT Analysis.

Lee Ju-Yeun, Choi Jae Hwan, Park Kyung-Ah, Oh Sei Yeul

Invest Ophthalmol Vis SciApr 201825 citationsCohort Study

Temporal GCIPL thinning in ethambutol-induced optic neuropathy predicts poorer vision recovery after drug cessation, highlighting its importance for visual prognosis.

Full abstract PubMed

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Lee Ju-Yeun

Using Machine Learning to Identify Ophthalmology Subspecialty Care and Advance Workforce Research with the IRIS® Registry (Intelligent Research in Sight).

Diagnostic value of ganglion cell-inner plexiform layer for early detection of ethambutol-induced optic neuropathy.

Ganglion Cell Layer and Inner Plexiform Layer as Predictors of Vision Recovery in Ethambutol-Induced Optic Neuropathy: A Longitudinal OCT Analysis.