Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Automated Identification of Diabetic Retinopathy Using Deep Learning
This map shows the geographic impact of Theodore Leng's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Theodore Leng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Theodore Leng more than expected).
This network shows the impact of papers produced by Theodore Leng. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Theodore Leng. The network helps show where Theodore Leng may publish in the future.
Co-authorship network of co-authors of Theodore Leng
This figure shows the co-authorship network connecting the top 25 collaborators of Theodore Leng.
A scholar is included among the top collaborators of Theodore Leng based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Theodore Leng. Theodore Leng is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Leng, Theodore, et al.. (2018). Automatic identification of referral-warranted diabetic retinopathy using deep learning on mobile phone images. Investigative Ophthalmology & Visual Science. 59(9). 1705–1705.1 indexed citations
Leng, Theodore, et al.. (2017). A deep learning approach for automatic identification of referral-warranted diabetic retinopathy. Investigative Ophthalmology & Visual Science. 58(8). 825–825.1 indexed citations
11.
Niu, Sijie, Luís de Sisternes, Qiang Chen, Theodore Leng, & Daniel L. Rubin. (2015). Automated Segmentation and Quantification in SD-OCT Images to Predict Future Geographic Atrophy Involvement. Investigative Ophthalmology & Visual Science. 56(7). 2839–2839.2 indexed citations
12.
Sher, Alexander, Loh-Shan Leung, Theodore Leng, et al.. (2010). Retinal Plasticity and Restoration of Function After Photocoagulation. Investigative Ophthalmology & Visual Science. 51(13). 2482–2482.3 indexed citations
Leng, Theodore, et al.. (2003). A Retinal Interface Based on Neurite Micropatterning for Single Cell Stimulation. Investigative Ophthalmology & Visual Science. 44(13). 5069–5069.2 indexed citations
17.
Leng, Theodore, et al.. (2003). Carbon Nanotube Bucky Paper as an Artificial Support Membrane and Bruch's Membrane Patch in Subretinal RPE and IPE Transplantation. Investigative Ophthalmology & Visual Science. 44(13). 481–481.3 indexed citations
18.
Leng, Theodore, et al.. (2002). The Artificial Synapse Chip: A Novel Interface for a Retinal Prosthesis based on Neurotransmitter Stimulation and Nerve Regeneration. Investigative Ophthalmology & Visual Science. 43(13). 2846–2846.2 indexed citations
19.
Leng, Theodore, et al.. (2002). Tissue Engineered Lens Capsule as a Substrate for IPE and RPE Transplantation. Investigative Ophthalmology & Visual Science. 43(13). 3452–3452.1 indexed citations
20.
Leng, Theodore, et al.. (2002). Directed Ganglion Cell Growth and Stimulation with Microcontact Printing as a Prototype Visual Prosthesis Interface. Investigative Ophthalmology & Visual Science. 43(13). 4454–4454.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.