Cai Wu

31 papers receiving 344 citations

Peers

Cai Wu
Comparison fields: 5 of 86
  • Statistics and Probability 47
  • Applied Psychology 18
  • Physiology 11
  • Hematology 25
  • Cancer Research 29
Replace Hyun Sook Oh with:
Hyun Sook Oh South Korea
Younghun Han United States
Martin Johnson United States
Nadia M. Penrod United States
Giusi Moffa Switzerland
Christopher Kaiser United States
Lingfu Zhang China
Pritibha Singh United States
Ivana Malenica United States
Yaozhong Liu China
Cai Wu relative to Hyun Sook Oh South Korea Hyun Sook Oh's profile →
Citations per field
00.5×5.5×
Hyun Sook Oh · 1×
Citations per year

Countries citing papers authored by Cai Wu

Since Specialization
Citations

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

Fields of papers citing papers by Cai Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201755
2 201450
3 201726
4 201725
5 201423
6 202122
7 201520
8 201916
9 202116
10 201915
11 201810
12 20199
13 20208
14
tdROC: Nonparametric estimation of time-dependent ROC curve from right censored survival data
20168
15 20207
16
EM clustering analysis of diabetes patients basic diagnosis index.
20056
17 20215
18
Development of a medical informatics data warehouse.
20065
19 20215
20 20174

About Cai Wu

Cai Wu is a scholar working on Statistics and Probability, Molecular Biology, Oncology, Management Science and Operations Research and Hepatology, having authored 34 papers that have together received 354 indexed citations. Recurring topics across this work include Statistical Methods in Clinical Trials (4 papers), Optimal Experimental Design Methods (3 papers), Hepatocellular Carcinoma Treatment and Prognosis (3 papers), Coffee research and impacts (2 papers), AI in cancer detection (2 papers), Statistical Methods and Inference (2 papers), Image Retrieval and Classification Techniques (2 papers) and Sarcoma Diagnosis and Treatment (1 paper). The work is most often cited by research in Statistics and Probability (47 citations), Applied Psychology (18 citations), Physiology (11 citations), Hematology (25 citations) and Cancer Research (29 citations). Cai Wu has collaborated with scholars based in China, United States and Taiwan. Frequent co-authors include Liang Li, Christine Vinci, Claire A. Spears, Diana S. Hoover, Heng Zhou, Cong Chen, He Huang, Qing Yi, Donald Hedeker and Yi Zhao. Their work appears in journals such as Abdominal Radiology, International Journal of Machine Learning and Cybernetics, Frontiers in Oncology, Contemporary Clinical Trials and Cancer Letters.

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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