Yan Chai Hum
- Radiology, Nuclear Medicine and Imaging top 5%
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Biomedical Engineering
- Rheumatology top 10%
- Co-authors
- Khin Wee LaiYee Kai TeeMaheza Irna Mohamad SalimTan Tian SweeWun‐She YapSamiappan DhanalakshmiEko SupriyantoJoon Huang Chuah
- Topics
- AI in cancer detection (17 papers)Radiomics and Machine Learning in Medical Imaging (14 papers)Medical Imaging and Analysis (10 papers)
In The Last Decade
Yan Chai Hum
79 papers receiving 712 citations
Peers
Comparison fields: 5 of 136
- Radiology, Nuclear Medicine and Imaging 243
- Computer Vision and Pattern Recognition 201
- Artificial Intelligence 172
- Biomedical Engineering 125
- Rheumatology 88
Countries citing papers authored by Yan Chai Hum
This map shows the geographic impact of Yan Chai Hum'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 Yan Chai Hum with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yan Chai Hum more than expected).
Fields of papers citing papers by Yan Chai Hum
This network shows the impact of papers produced by Yan Chai Hum. 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 Yan Chai Hum. The network helps show where Yan Chai Hum may publish in the future.
Co-authorship network of co-authors of Yan Chai Hum
This figure shows the co-authorship network connecting the top 25 collaborators of Yan Chai Hum. A scholar is included among the top collaborators of Yan Chai Hum based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Yan Chai Hum. Yan Chai Hum is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 3 | |
| 6 | 1 | |
| 7 | 0 | |
| 8 | 4 | |
| 9 | 11 | |
| 10 | 2 | |
| 11 | 5 | |
| 12 | Three dimensional nuchal translucency assessment using magnetic resonance reconstruction imaging | 1 |
| 13 | Edge detection in ultrasound images using speckle reducing anisotropic diffusion in canny edge detector framework | 11 |
| 14 | 21 | |
| 15 | 4 | |
| 16 | Surface rendering of three dimensional ultrasound images using VTK | 19 |
| 17 | 2 | |
| 18 | 5 | |
| 19 | Ultrasound Images Edge Detection using Anisotropic Diffusion in Canny Edge Detector Framework | 6 |
| 20 | GLCM based adaptive crossed reconstructed (ACR) k-mean clustering hand bone segmentation | 11 |
About Yan Chai Hum
Yan Chai Hum is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Media Technology, having authored 90 papers that have together received 757 indexed citations. Recurring topics across this work include AI in cancer detection (17 papers), Radiomics and Machine Learning in Medical Imaging (14 papers) and Medical Imaging and Analysis (10 papers). The work is most often cited by research in Health Informatics (24 citations), Radiology, Nuclear Medicine and Imaging (243 citations) and Computer Vision and Pattern Recognition (201 citations). Yan Chai Hum has collaborated with scholars based in Malaysia, Sweden and China. Frequent co-authors include Khin Wee Lai, Yee Kai Tee, Maheza Irna Mohamad Salim, Tan Tian Swee, Wun‐She Yap, Samiappan Dhanalakshmi, Eko Supriyanto, Joon Huang Chuah, Khairunnisa Hasikin and Belinda Pingguan‐Murphy. Their work appears in journals such as Scientific Reports, Magnetic Resonance in Medicine and Expert Systems with Applications.
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.