Daniel Ting

1.2k citations
20 papers · 545 indexed · h-index 11

Impact in

Papers in

    • Retinal Diseases and Treatments 13
    • Glaucoma and retinal disorders 7
    • Retinal and Optic Conditions 6
    • Artificial Intelligence in Healthcare and Education 2

Daniel Ting

17 papers receiving 538 citations

Peers

Daniel Ting
Comparison fields: 5 of 71
  • Ophthalmology 408
  • Radiology, Nuclear Medicine and Imaging 402
  • Health Informatics 11
  • Health Information Management 28
  • Clinical Biochemistry 18
Replace Ryan T. Yanagihara with:
Ryan T. Yanagihara United States
Zhi Da Soh Singapore
Dana M. Blumberg United States
Hagar Khalid United Kingdom
Fangyao Tang Hong Kong
Bin Lv China
Eduardo B. Mariottoni United States
Peng Guan Ong Singapore
Poemen P. Chan Hong Kong
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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
#Work
1 2016114
2 202080
3 201764
4 202062
5 202161
6 201155
7 201124
8 202221
9 201016
10
Diabetic retinopathy--screening and management by Australian GPs.
201114
11 202112
12 20118
13 20245
14 20233
15 20133
16
Estimation of Haemoglobin A1c from Retinal photographs via Deep Learning.
20192
17 20121
18 20250
19 20200
20
Classic Risk Factors for Diabetic Retinopathy: Deep Learning versus Human Graders
20180

About Daniel Ting

Daniel Ting is a scholar working on Ophthalmology, Health Informatics, Radiology, Nuclear Medicine and Imaging, Health Information Management and Epidemiology, having authored 20 papers that have together received 545 indexed citations. Recurring topics across this work include Retinal Imaging and Analysis (16 papers), Retinal Diseases and Treatments (13 papers), Glaucoma and retinal disorders (7 papers), Retinal and Optic Conditions (6 papers), Acute Ischemic Stroke Management (2 papers), Artificial Intelligence in Healthcare and Education (2 papers), Ophthalmology and Visual Impairment Studies (2 papers) and Optical Coherence Tomography Applications (1 paper). The work is most often cited by research in Ophthalmology (408 citations), Radiology, Nuclear Medicine and Imaging (402 citations), Health Informatics (11 citations), Health Information Management (28 citations) and Clinical Biochemistry (18 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, Charumathi Sabanayagam, Wanfen Yip, Valentina Bellemo, Yuchen Xie, Marcus Ang, Gilbert Lim, Carol Y. Cheung and Yogesan Kanagasingam. Their work appears in journals such as Eye and Vision, Ophthalmology, Eye, Clinical and Experimental Ophthalmology and Scientific Reports.

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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