Kyle Lam
- Health Informatics top 0.1%
- Artificial Intelligence in Healthcare and Education 10
- Family Practice top 5%
- Neurology top 5%
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- Radiomics and Machine Learning in Medical Imaging 2
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- Surgical Simulation and Training 9
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- Cardiac, Anesthesia and Surgical Outcomes 4
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- Machine Learning in Healthcare 3
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- Healthcare cost, quality, practices 3
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- Digital Imaging in Medicine 3
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- Climate Change and Health Impacts 2
- Co-authors
- Ara DarziFahad IqbalHutan AshrafianJonathan ClarkeViknesh SounderajahSanjay PurkayasthaJames KinrossBenny Lo
- Journals
- EClinicalMedicine (4 papers)Journal of Medical Internet Research (3 papers)The Lancet Digital Health (2 papers)
- Partner nations
- United KingdomUnited StatesHong Kong
In The Last Decade
Kyle Lam
29 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 135
- Health Informatics 473
- Family Practice 42
- Neurology 199
- Health Information Management 55
- Radiology, Nuclear Medicine and Imaging 245
Countries citing papers authored by Kyle Lam
This map shows the geographic impact of Kyle 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 Kyle Lam with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kyle Lam more than expected).
Fields of papers citing papers by Kyle Lam
This network shows the impact of papers produced by Kyle 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 Kyle Lam. The network helps show where Kyle Lam may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Kyle 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
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 1 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 0 | |
| 4 | 2024 | 1 | |
| 5 | 2024 | 3 | |
| 6 | LLM-based agentic systems in medicine and healthcarebreakdown → | 2024 | 48 |
| 7 | 2024 | 12 | |
| 8 | 2024 | 2 | |
| 9 | 2023 | 11 | |
| 10 | 2023 | 12 | |
| 11 | 2023 | 14 | |
| 12 | 2023 | 7 | |
| 13 | 2023 | 111 | |
| 14 | 2022 | 1 | |
| 15 | 2022 | 8 | |
| 16 | 2022 | 4 | |
| 17 | 2021 | 20 | |
| 18 | Characteristics and predictors of acute and chronic post-COVID syndrome: A systematic review and meta-analysisbreakdown → | 2021 | 211 |
| 19 | 2021 | 55 | |
| 20 | 2021 | 9 |
About Kyle Lam
Kyle Lam is a scholar working on Health Informatics, Surgery, General Health Professions, Cardiology and Cardiovascular Medicine and Health Information Management, having authored 32 papers that have together received 1.2k indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare and Education (10 papers), Surgical Simulation and Training (9 papers), Cardiac, Anesthesia and Surgical Outcomes (4 papers), Machine Learning in Healthcare (3 papers), Healthcare cost, quality, practices (3 papers), Digital Imaging in Medicine (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and Climate Change and Health Impacts (2 papers). The work is most often cited by research in Health Informatics (473 citations), Family Practice (42 citations), Neurology (199 citations), Health Information Management (55 citations) and Radiology, Nuclear Medicine and Imaging (245 citations). Kyle Lam has collaborated with scholars based in United Kingdom, United States and Hong Kong. Frequent co-authors include Ara Darzi, Fahad Iqbal, Hutan Ashrafian, Jonathan Clarke, Viknesh Sounderajah, Sanjay Purkayastha, James Kinross, Benny Lo, Wu Yuan and Jianing Qiu. Their work appears in journals such as EClinicalMedicine, Journal of Medical Internet Research, The Lancet Digital Health, npj Digital Medicine and The Lancet Regional Health - Western Pacific.
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.