Saikit Lam
Impact in
- Health Informatics top 5%
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- Radiomics and Machine Learning in Medical Imaging
- Medical Imaging Techniques and Applications
- MRI in cancer diagnosis
Papers in
-
- Radiomics and Machine Learning in Medical Imaging 30
- MRI in cancer diagnosis 9
- Medical Imaging Techniques and Applications 8
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- Lung Cancer Diagnosis and Treatment 8
- Co-authors
- Jing Cai (38 shared papers)Jiang Zhang (21 shared papers)Qilin Zhang (1 shared paper)Kwok‐Hung Au (12 shared papers)Ta Zhou (11 shared papers)Ruijie Yang (2 shared papers)Xinzhi Teng (16 shared papers)Zongrui Ma (9 shared papers)
- Journals
- Frontiers in Oncology (7 papers)Cancers (4 papers)International Journal of Radiation Oncology*Biology*Physics (3 papers)Medical Physics (2 papers)Scientific Reports (2 papers)
- Partner nations
- Hong KongChinaUnited States
In The Last Decade
Saikit Lam
48 papers receiving 739 citations
Peers
Comparison fields: 5 of 103
- Health Informatics 41
- Radiology, Nuclear Medicine and Imaging 488
- Radiation 173
- Otorhinolaryngology 76
- Pulmonary and Respiratory Medicine 198
Countries citing papers authored by Saikit Lam
This map shows the geographic impact of Saikit Lam'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 Saikit Lam with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Saikit Lam more than expected).
Fields of papers citing papers by Saikit Lam
This network shows the impact of papers produced by Saikit Lam. 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 Saikit Lam. The network helps show where Saikit Lam may publish in the future.
Co-authors
The 25 scholars most cited alongside Saikit Lam, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 53 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 98 | |
| 2 | 2023 | 92 | |
| 3 | 2020 | 57 | |
| 4 | 2019 | 47 | |
| 5 | 2021 | 32 | |
| 6 | 1994 | 29 | |
| 7 | 2023 | 28 | |
| 8 | 2024 | 25 | |
| 9 | 2022 | 23 | |
| 10 | 2023 | 22 | |
| 11 | 2022 | 22 | |
| 12 | 2022 | 19 | |
| 13 | 1998 | 18 | |
| 14 | 2022 | 18 | |
| 15 | 2021 | 17 | |
| 16 | 2023 | 16 | |
| 17 | 2021 | 16 | |
| 18 | 2022 | 14 | |
| 19 | 2023 | 13 | |
| 20 | 2023 | 12 |
About Saikit Lam
Saikit Lam is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Radiation, Otorhinolaryngology and Artificial Intelligence, having authored 53 papers that have together received 749 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (30 papers), Advanced Radiotherapy Techniques (12 papers), Head and Neck Cancer Studies (10 papers), MRI in cancer diagnosis (9 papers), Medical Imaging Techniques and Applications (8 papers), Lung Cancer Diagnosis and Treatment (8 papers), AI in cancer detection (7 papers) and Hepatocellular Carcinoma Treatment and Prognosis (3 papers). The work is most often cited by research in Health Informatics (41 citations), Radiology, Nuclear Medicine and Imaging (488 citations), Radiation (173 citations), Otorhinolaryngology (76 citations) and Pulmonary and Respiratory Medicine (198 citations). Saikit Lam has collaborated with scholars based in Hong Kong, China and United States. Frequent co-authors include Jing Cai, Jiang Zhang, Qilin Zhang, Kwok‐Hung Au, Ta Zhou, Ruijie Yang, Xinzhi Teng, Zongrui Ma, Yuanpeng Zhang and Bing Li. Their work appears in journals such as Frontiers in Oncology, Cancers, International Journal of Radiation Oncology*Biology*Physics, Medical Physics and Scientific Reports.
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.