Ling Dai

2.0k total citations · 1 hit paper
10 papers, 566 citations indexed

About

Ling Dai is a scholar working on Ophthalmology, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition. According to data from OpenAlex, Ling Dai has authored 10 papers receiving a total of 566 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Ophthalmology, 5 papers in Radiology, Nuclear Medicine and Imaging and 2 papers in Computer Vision and Pattern Recognition. Recurrent topics in Ling Dai's work include Retinal Imaging and Analysis (5 papers), Retinal Diseases and Treatments (4 papers) and Retinal and Optic Conditions (3 papers). Ling Dai is often cited by papers focused on Retinal Imaging and Analysis (5 papers), Retinal Diseases and Treatments (4 papers) and Retinal and Optic Conditions (3 papers). Ling Dai collaborates with scholars based in China, Hong Kong and United States. Ling Dai's co-authors include Huating Li, Weiping Jia, Qiang Wu, Xuhong Hou, Bin Sheng, Ruogu Fang, Bin Sheng, Dinggang Shen, Hongyu Kong and Xiangning Wang and has published in prestigious journals such as Nature Communications, IEEE Transactions on Medical Imaging and Medical Image Analysis.

In The Last Decade

Ling Dai

9 papers receiving 543 citations

Hit Papers

align trajectories

What are hit papers?

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.

A deep learning system for detecting diabetic retinopathy across the disease spectrum

2021 319 citations Ling Dai, Liang Wu et al. Nature Communications profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Ling Dai China	6	417	277	189	103	92	10	566
Samiksha Pachade United States	7	756 1.8×	495 1.8×	365 1.9×	127 1.2×	115 1.3×	12	827
Rubina Sarki Australia	6	299 0.7×	135 0.5×	139 0.7×	70 0.7×	83 0.9×	7	393
A. Krishna Rao India	7	492 1.2×	348 1.3×	247 1.3×	50 0.5×	65 0.7×	9	593
Bruno Laÿ United States	7	1.1k 2.7×	812 2.9×	629 3.3×	189 1.8×	157 1.7×	20	1.3k
Jahanzaib Latif China	8	185 0.4×	79 0.3×	93 0.5×	54 0.5×	106 1.2×	9	338
Parham Khojasteh Australia	7	212 0.5×	134 0.5×	104 0.6×	56 0.5×	35 0.4×	8	292
Neha Gour India	9	253 0.6×	160 0.6×	168 0.9×	28 0.3×	45 0.5×	17	334
Kevin Noronha India	12	561 1.3×	436 1.6×	311 1.6×	43 0.4×	54 0.6×	26	644
Swamidoss Issac Niwas India	14	279 0.7×	202 0.7×	212 1.1×	19 0.2×	140 1.5×	19	499
Along He China	6	289 0.7×	140 0.5×	248 1.3×	46 0.4×	128 1.4×	14	518

Countries citing papers authored by Ling Dai

Since Specialization

Citations

This map shows the geographic impact of Ling Dai'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 Ling Dai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ling Dai more than expected).

Fields of papers citing papers by Ling Dai

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ling Dai. 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 Ling Dai. The network helps show where Ling Dai may publish in the future.

Co-authorship network of co-authors of Ling Dai

This figure shows the co-authorship network connecting the top 25 collaborators of Ling Dai. A scholar is included among the top collaborators of Ling Dai 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 Ling Dai. Ling Dai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

10 of 10 papers shown

1.

Dai, Ling, Yanfang Guo, Liang Zhong, et al.. (2025). An integrin-based quercetin 7-rhamnoside liver-targeted delivery liposomes for intrahepatic cholestasis in pregnancy. Materials Today Bio. 33. 102031–102031.

2.

Li, Jiajia, Ling Dai, Hui Shen, et al.. (2022). CDX-NET: Cross-Domain Multi-Feature Fusion Modeling Via Deep Neural Networks for Multivariate Time Series Forecasting in AIOps. ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 4073–4077. 1 indexed citations

3.

Dai, Ling, Liang Wu, Huating Li, et al.. (2021). A deep learning system for detecting diabetic retinopathy across the disease spectrum. Nature Communications. 12(1). 3242–3242. 319 indexed citations breakdown →

4.

Guo, Hai, et al.. (2021). Offline Printed Tai Le Character Recognition Using VGGNET. 61. 117–121. 1 indexed citations

5.

Sheng, Bin, Ruogu Fang, Huating Li, et al.. (2020). Domain-invariant interpretable fundus image quality assessment. Medical Image Analysis. 61. 101654–101654. 66 indexed citations

6.

Pan, Siyuan, Ling Dai, Xuhong Hou, Huating Li, & Bin Sheng. (2020). ChefGAN. 4244–4252. 19 indexed citations

7.

Wang, Xiangning, Ling Dai, Shu‐Ting Li, et al.. (2020). Automatic Grading System for Diabetic Retinopathy Diagnosis Using Deep Learning Artificial Intelligence Software. Current Eye Research. 45(12). 1550–1555. 23 indexed citations

8.

Dai, Ling, Ruogu Fang, Huating Li, et al.. (2018). Clinical Report Guided Retinal Microaneurysm Detection With Multi-Sieving Deep Learning. IEEE Transactions on Medical Imaging. 37(5). 1149–1161. 125 indexed citations

9.

Dai, Ling, et al.. (2017). Automatic diabetic retinopathy diagnosis using adjustable ophthalmoscope and multi-scale line operator. Pervasive and Mobile Computing. 41. 490–503. 8 indexed citations

10.

Wu, Zhenhua, et al.. (2008). Analysis of load characteristic of typical user of urban distribution networks. 1–5. 4 indexed citations

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.

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