Keng Yeow Tay

1.2k citations
34 papers · 957 indexed · 1 hit paper · h-index 12

Keng Yeow Tay

29 papers receiving 938 citations

Hit Papers

Incremental Support Vector Learning for Ordinal Regression6072014202620182022200400600

Peers

Keng Yeow Tay
Comparison fields: 5 of 128
  • Computer Vision and Pattern Recognition 237
  • Health Informatics 12
  • Artificial Intelligence 282
  • Media Technology 51
  • Neurology 87
Replace Wee Kheng Leow with:
Wee Kheng Leow Singapore
Xiaoguang Li China
Xi Wu China
Yuan Tian China
Dong Zhao China
Junding Sun China
Jamshid Dehmeshki United Kingdom
Pavel Lyakhov Russia
Hong Song China
Keng Yeow Tay relative to Wee Kheng Leow Singapore Wee Kheng Leow's profile →
Citations per field
00.5×4.3×
Wee Kheng Leow · 1×
Citations per year

Countries citing papers authored by Keng Yeow Tay

Since Specialization
Citations

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

Fields of papers citing papers by Keng Yeow Tay

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Keng Yeow Tay. 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 Keng Yeow Tay. The network helps show where Keng Yeow Tay may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20243
2 20240
3 20231
4 20222
5 20220
6 20220
7 20211
8 202112
9 20195
10 20189
11 201710
12 20172
13 201610
14 201657
15 201410
16 201419
17 20134
18 20126
19 201216
20 200542

About Keng Yeow Tay

Keng Yeow Tay is a scholar working on Health Informatics, Radiation and Neurology, having authored 34 papers that have together received 957 indexed citations. Recurring topics across this work include Advanced Radiotherapy Techniques (5 papers), Radiology practices and education (5 papers), Mitochondrial Function and Pathology (4 papers), Brain Metastases and Treatment (3 papers), Metabolism and Genetic Disorders (3 papers), Glioma Diagnosis and Treatment (3 papers), Advances in Oncology and Radiotherapy (3 papers) and Intracranial Aneurysms: Treatment and Complications (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (237 citations), Health Informatics (12 citations) and Artificial Intelligence (282 citations). Keng Yeow Tay has collaborated with scholars based in Canada, United States and United Kingdom. Frequent co-authors include Victor S. Sheng, Shuo Li, Walter Romano, Bin Gu, Bin Gu, Jonathan H. Gillard, David A. Palma, Nicholas J. Higgins, Eun‐Jeong Yu and Nagui M. Antoun. Their work appears in journals such as Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques, International Journal of Radiation Oncology*Biology*Physics, European Radiology, Frontiers in Neurology and Multiple Sclerosis and Related Disorders.

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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