Kai-Bo Duan

1.5k citations
4 papers · 513 indexed · 1 hit paper · h-index 3

Kai-Bo Duan

4 papers receiving 486 citations

Hit Papers

Evaluation of simple performance measures for tuning SVM ...4662003202620102018100200300400

Peers

Kai-Bo Duan
Comparison fields: 5 of 106
  • Computer Vision and Pattern Recognition 151
  • Artificial Intelligence 184
  • Analytical Chemistry 32
  • Control and Systems Engineering 73
  • Management Science and Operations Research 37
Replace Saúl Solorio-Fernández with:
Saúl Solorio-Fernández Mexico
André Luis Debiaso Rossi Brazil
G. Maragatham India
K. Ganesan India
Manas Ranjan Senapati India
Adriaan Lambrechts Belgium
Hanen Borchani Spain
Jian Xiao China
Youssef Ghanou Morocco
Mahmoud B. Alhasanat Jordan
Kai-Bo Duan relative to Saúl Solorio-Fernández Mexico Saúl Solorio-Fernández's profile →
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Saúl Solorio-Fernández · 1×
Citations per year

Countries citing papers authored by Kai-Bo Duan

Since Specialization
Citations

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

Fields of papers citing papers by Kai-Bo Duan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kai-Bo Duan. 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 Kai-Bo Duan. The network helps show where Kai-Bo Duan may publish in the future.

Co-authorship network

The 7 scholars most cited alongside Kai-Bo Duan, 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 Kai-Bo Duan Line = papers co-authored together Kai-Bo Duan links everyone, so they are left out of the graph.

All Works

4 of 4 papers shown
#Work
1
Genomic analysis of TGFβ treated cell lines with phenotypically distinct outcomes to identify transcriptional signatures for assessment in stratification of cancers
20071
2 200529
3 200517
4
Evaluation of simple performance measures for tuning SVM hyperparametersbreakdown →
2003466

About Kai-Bo Duan

Kai-Bo Duan is a scholar working on Spectroscopy, Signal Processing and Pathology and Forensic Medicine, having authored 4 papers that have together received 513 indexed citations. Recurring topics across this work include Metabolomics and Mass Spectrometry Studies (2 papers), Advanced Proteomics Techniques and Applications (2 papers), Mass Spectrometry Techniques and Applications (2 papers), Pancreatic and Hepatic Oncology Research (1 paper), Genetic factors in colorectal cancer (1 paper), TGF-β signaling in diseases (1 paper), Neural Networks and Applications (1 paper) and Blind Source Separation Techniques (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (151 citations), Artificial Intelligence (184 citations) and Analytical Chemistry (32 citations). Kai-Bo Duan has collaborated with scholars based in Singapore. Frequent co-authors include A.N. Poo, S. Sathiya Keerthi, Jagath C. Rajapakse, Lei Yan, Jonathan M. Yingling, Jianyong Shou and Ketan Patel. Their work appears in journals such as Clinical Cancer Research, Neurocomputing and PubMed.

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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