Khin Wee Lai
- Radiology, Nuclear Medicine and Imaging top 2%
- Biomedical Engineering top 10%
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 2%
- Cardiology and Cardiovascular Medicine top 10%
- Co-authors
- Yan Chai HumSamiappan DhanalakshmiKhairunnisa HasikinEko SupriyantoBelinda Pingguan‐MurphyAzira KhalilYee Kai TeeJoon Huang Chuah
- Topics
- Radiomics and Machine Learning in Medical Imaging (19 papers)AI in cancer detection (19 papers)Cardiac Valve Diseases and Treatments (12 papers)
In The Last Decade
Khin Wee Lai
167 papers receiving 2.1k citations
Peers
Comparison fields: 5 of 173
- Radiology, Nuclear Medicine and Imaging 646
- Biomedical Engineering 474
- Artificial Intelligence 410
- Computer Vision and Pattern Recognition 395
- Cardiology and Cardiovascular Medicine 176
Countries citing papers authored by Khin Wee Lai
This map shows the geographic impact of Khin Wee Lai'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 Khin Wee Lai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Khin Wee Lai more than expected).
Fields of papers citing papers by Khin Wee Lai
This network shows the impact of papers produced by Khin Wee Lai. 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 Khin Wee Lai. The network helps show where Khin Wee Lai may publish in the future.
Co-authorship network of co-authors of Khin Wee Lai
This figure shows the co-authorship network connecting the top 25 collaborators of Khin Wee Lai. A scholar is included among the top collaborators of Khin Wee Lai 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 Khin Wee Lai. Khin Wee Lai 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 | 3 | |
| 4 | 1 | |
| 5 | 0 | |
| 6 | 1 | |
| 7 | 7 | |
| 8 | 26 | |
| 9 | 1 | |
| 10 | 6 | |
| 11 | 10 | |
| 12 | 15 | |
| 13 | 11 | |
| 14 | Three dimensional nuchal translucency assessment using magnetic resonance reconstruction imaging | 1 |
| 15 | Segmentation of prostate tumor for gamma image using region growing method | 3 |
| 16 | Edge detection in ultrasound images using speckle reducing anisotropic diffusion in canny edge detector framework | 11 |
| 17 | 21 | |
| 18 | 4 | |
| 19 | Automated trisomy 21 assessment based on maternal serum markers using trivariate lognormal distribution | 2 |
| 20 | 21 |
About Khin Wee Lai
Khin Wee Lai is a scholar working on Medical Laboratory Technology, Radiology, Nuclear Medicine and Imaging and Health Information Management, having authored 182 papers that have together received 2.2k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (19 papers), AI in cancer detection (19 papers) and Cardiac Valve Diseases and Treatments (12 papers). The work is most often cited by research in Health Informatics (71 citations), Medical Laboratory Technology (61 citations) and Radiology, Nuclear Medicine and Imaging (646 citations). Khin Wee Lai has collaborated with scholars based in Malaysia, China and India. Frequent co-authors include Yan Chai Hum, Samiappan Dhanalakshmi, Khairunnisa Hasikin, Eko Supriyanto, Belinda Pingguan‐Murphy, Azira Khalil, Yee Kai Tee, Joon Huang Chuah, Siew‐Cheok Ng and Maheza Irna Mohamad Salim. Their work appears in journals such as ACS Nano, PLoS ONE and Advanced Functional Materials.
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.