Daniel Ting

1.3k citations
24 papers · 610 · h-index 11

Impact in

Papers in

Daniel Ting

23 papers receiving 600 citations

Peers

Daniel Ting
Comparison fields: 5 of 65
  • Ophthalmology 349
  • Radiology, Nuclear Medicine and Imaging 308
  • Health Informatics 14
  • Health Information Management 28
  • Cognitive Neuroscience 54
Replace Cason B. Robbins with:
Cason B. Robbins United States
Sonja Karst Austria
Ryan T. Yanagihara United States
Hagar Khalid United Kingdom
Yan Tong China
Zhi Da Soh Singapore
Sandrina Nunes Portugal
Geunyoung Lee Singapore
Skylar E. Stolte United States
Alessandro A. Jammal United States
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Citations per field
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Citations per year

Countries citing papers authored by Daniel Ting

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Ting

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Daniel Ting, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Daniel Ting Line = papers co-authored together Daniel Ting links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016119
2 202087
3 202069
4 201766
5 202165
6 201161
7 201125
8 202222
9 201016
10
Diabetic retinopathy--screening and management by Australian GPs.
201114
11 202112
12 20249
13 20119
14 20219
15 20218
16 20196
17 20233
18 20133
19 20252
20
Estimation of Haemoglobin A1c from Retinal photographs via Deep Learning.
20192

About Daniel Ting

Daniel Ting is a scholar working on Ophthalmology, Radiology, Nuclear Medicine and Imaging, Health Informatics, Epidemiology and Biomedical Engineering, having authored 24 papers that have together received 610 indexed citations. Recurring topics across this work include Retinal Diseases and Treatments (12 papers), Retinal Imaging and Analysis (10 papers), Retinal and Optic Conditions (6 papers), Glaucoma and retinal disorders (3 papers), Ophthalmology and Visual Impairment Studies (2 papers), Artificial Intelligence in Healthcare and Education (2 papers), Optical Coherence Tomography Applications (1 paper) and Radiomics and Machine Learning in Medical Imaging (1 paper). The work is most often cited by research in Ophthalmology (349 citations), Radiology, Nuclear Medicine and Imaging (308 citations), Health Informatics (14 citations), Health Information Management (28 citations) and Cognitive Neuroscience (54 citations). Daniel Ting has collaborated with scholars based in Singapore, Australia and United Kingdom. Frequent co-authors include Tien Yin Wong, Gavin Siew Wei Tan, Wanfen Yip, Charumathi Sabanayagam, Valentina Bellemo, Gilbert Lim, Marcus Ang, Yuchen Xie, Carol Y. Cheung and Yogesan Kanagasingam. Their work appears in journals such as Clinical and Experimental Ophthalmology, Ophthalmology, Eye and Vision, Ophthalmic Epidemiology and Eye.

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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