Peng Cao

35 papers receiving 788 citations

Peers

Peng Cao
Comparison fields: 5 of 102
  • Computational Mathematics 12
  • Health Information Management 62
  • Neurology 86
  • Artificial Intelligence 341
  • Radiology, Nuclear Medicine and Imaging 216
Replace S. Vinitha Sree with:
S. Vinitha Sree Singapore
Loc Tran United States
Donghuan Lu China
Alexandre Savio Spain
Siqi Liu China
Jialin Peng China
Jacob Furst United States
Zhuangzhi Yan China
Jingyu Liu China
Ebrahim Mohammed Senan Saudi Arabia
Peng Cao relative to S. Vinitha Sree Singapore S. Vinitha Sree's profile →
Citations per field
00.5×
S. Vinitha Sree · 1×
Citations per year

Countries citing papers authored by Peng Cao

Since Specialization
Citations

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

Fields of papers citing papers by Peng Cao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020161
2 2022113
3 201658
4 201744
5 202139
6 201339
7 201833
8 201730
9 201630
10 202224
11 201821
12 202220
13 201819
14 201917
15 201816
16 202215
17 202314
18 202214
19 201612
20 202112

About Peng Cao

Peng Cao is a scholar working on Artificial Intelligence, Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging, Health Information Management and Psychiatry and Mental health, having authored 37 papers that have together received 800 indexed citations. Recurring topics across this work include Imbalanced Data Classification Techniques (10 papers), Functional Brain Connectivity Studies (8 papers), Artificial Intelligence in Healthcare (6 papers), Retinal Imaging and Analysis (5 papers), Dementia and Cognitive Impairment Research (5 papers), Domain Adaptation and Few-Shot Learning (4 papers), Electricity Theft Detection Techniques (4 papers) and Brain Tumor Detection and Classification (3 papers). The work is most often cited by research in Computational Mathematics (12 citations), Health Information Management (62 citations), Neurology (86 citations), Artificial Intelligence (341 citations) and Radiology, Nuclear Medicine and Imaging (216 citations). Peng Cao has collaborated with scholars based in China, Canada and Singapore. Frequent co-authors include Osmar R. Zai͏̈ane, Jinzhu Yang, Dazhe Zhao, Xiaoli Liu, Min Huang, Dina Katabi, Rogério Feris, Lijie Fan, Yuzhe Yang and Tianhong Li. Their work appears in journals such as Computerized Medical Imaging and Graphics, Computers in Biology and Medicine, Computer Methods and Programs in Biomedicine, Neuroinformatics and ACM Transactions on Knowledge Discovery from Data.

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.

Explore authors with similar magnitude of impact