Luis J. Mejico

Pilot corpus only

This score is computed over theSindex pilot corpus and does not cover the full scientific literature. Scores are relative to papers we have ingested — papers, authors, and institutions outside the pilot are not represented. Methodology.

Top 100%percentile

0Author DataRank

Indexed papers

0in pilot corpus

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Papers

Driven by 3 papers. Top paper: “Accuracy of a Deep Learning System for Classification of Papilledema Severity on Ocular Fundus Photographs”.

Accuracy of a Deep Learning System for Classification of Papilledema Severity on Ocular Fundus Photographs

Neurology(2021)10.1212/wnl.0000000000012226

N/A

0DataRank · unranked

67 citations

Raymond P. Najjar, Xinxing Xu, Zhiqun Tang, Jing Liang Loo, Shweta Singhal +64 more

Application of a Deep Learning System to Detect Papilledema on Nonmydriatic Ocular Fundus Photographs in an Emergency Department

American Journal of Ophthalmology(2023)10.1016/j.ajo.2023.10.025

N/A

0DataRank · unranked

33 citations

Raymond P. Najjar, Zhiqun Tang, Mung Yan Lin, David W. Wright, Matthew Keadey +73 more

The BONSAI (Brain and Optic Nerve Study with Artificial Intelligence) deep learning system can accurately identify pediatric papilledema on standard ocular fundus photographs

Journal of American Association for Pediatric Ophthalmology and Strabismus(2024)10.1016/j.jaapos.2023.10.005

N/A

0DataRank · unranked

20 citations

Raymond P. Najjar, Zhiqun Tang, Daniela Cioplean, Mihaela Dragomir, Audrey Chia +73 more