Yiming Ding

735 citations
9 papers · 486 · 1 hit paper · h-index 6

Impact in

    • Artificial Intelligence in Healthcare and Education
  • Neurology top 10%
    • Brain Tumor Detection and Classification

Papers in

Yiming Ding

6 papers receiving 466 citations

Yiming Ding's Hit Papers

A Deep Learning Model to Predict a Diagnosis of Alzheimer Disease by Using 18F-FDG PET of the Brain 2018 · 422 citations
4220+2+5Years since publication100200300400

Peers

Yiming Ding
Comparison fields: 5 of 88
  • Health Informatics 50
  • Neurology 115
  • Health Information Management 57
  • Psychiatry and Mental health 94
  • Radiology, Nuclear Medicine and Imaging 136
Replace Shangran Qiu with:
Shangran Qiu United States
Michael Kawczynski United States
Colin Magdamo United States
Saori Koshino Japan
Pauline Mouchès Canada
Tzu-An Song United States
T. Whyntie United Kingdom
M. Ethan MacDonald Canada
Jinseong Jang South Korea
Salman Seyedi United States
Yiming Ding relative to Shangran Qiu United States Shangran Qiu's profile →
Citations per field
00.5×4.5×
Shangran Qiu · 1×
Citations per year

Countries citing papers authored by Yiming Ding

Since Specialization
Citations

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

Fields of papers citing papers by Yiming Ding

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Yiming Ding, 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 Yiming Ding Line = papers co-authored together Yiming Ding links everyone, so they are left out of the graph.

All Works

9 of 9 papers shown
#Work
1
A Deep Learning Model to Predict a Diagnosis of Alzheimer Disease by Using 18F-FDG PET of the Brain
Hit paper breakdown →
2018422
2 201224
3 201016
4 201012
5 20237
6 20145
7 20250
8 20240
9 20250

About Yiming Ding

Yiming Ding is a scholar working on Atomic and Molecular Physics, and Optics, Electrical and Electronic Engineering, Cardiology and Cardiovascular Medicine, Pulmonary and Respiratory Medicine and Computer Vision and Pattern Recognition, having authored 9 papers that have together received 486 indexed citations. Recurring topics across this work include Advanced Fiber Laser Technologies (3 papers), Laser-Matter Interactions and Applications (2 papers), Photonic and Optical Devices (2 papers), Semiconductor Lasers and Optical Devices (2 papers), Semiconductor Quantum Structures and Devices (2 papers), Vacuum and Plasma Arcs (2 papers), Metal and Thin Film Mechanics (1 paper) and Electrical Contact Performance and Analysis (1 paper). The work is most often cited by research in Health Informatics (50 citations), Neurology (115 citations), Health Information Management (57 citations), Psychiatry and Mental health (94 citations) and Radiology, Nuclear Medicine and Imaging (136 citations). Yiming Ding has collaborated with scholars based in China, United Kingdom and France. Frequent co-authors include Miguel Hernandez Pampaloni, Michael Kawczynski, Roy Harnish, Carina Marí Aparici, Robert R. Flavell, Spencer C. Behr, Mariam Aboian, Lorenzo Nardo, Randall A. Hawkins and Dmytro Lituiev. Their work appears in journals such as IEEE Transactions on Plasma Science, Radiology, Physics of Plasmas, Applied Physics Letters and Journal of Clinical Hypertension.

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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