M. Lam
Impact in
- Neurology top 5%
- Long-Term Effects of COVID-19
-
- Intensive Care Unit Cognitive Disorders
Papers in
-
- Machine Learning in Bioinformatics 1
- Biochemical and Structural Characterization 1
- Genomics and Phylogenetic Studies 1
- Co-authors
- Yun Kwok Wing (3 shared papers)Steven Wai Ho Chau (1 shared paper)Adam Zemła (2 shared papers)Hairong Nan (1 shared paper)Linong Ji (1 shared paper)Rose Z.W. Ting (1 shared paper)Roseanne O. Yeung (1 shared paper)Juliana C.N. Chan (1 shared paper)
- Journals
- Canadian Journal of Cardiology (1 paper)Journal of Affective Disorders (1 paper)General Hospital Psychiatry (1 paper)Nucleic Acids Research (1 paper)PLoS ONE (1 paper)
- Partner nations
- Hong KongChinaUnited States
In The Last Decade
M. Lam
8 papers receiving 607 citations
M. Lam's Hit Papers
Peers
Comparison fields: 5 of 75
- Neurology 396
- Critical Care and Intensive Care Medicine 82
- Clinical Psychology 331
- Biological Psychiatry 29
- Psychiatry and Mental health 133
Countries citing papers authored by M. Lam
This map shows the geographic impact of M. 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 M. Lam with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. Lam more than expected).
Fields of papers citing papers by M. Lam
This network shows the impact of papers produced by M. 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 M. Lam. The network helps show where M. Lam may publish in the future.
Co-authors
The 25 scholars most cited alongside M. 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 | Mental Morbidities and Chronic Fatigue in Severe Acute Respiratory Syndrome Survivors Hit paper breakdown → | 2009 | 514 |
| 2 | 2013 | 48 | |
| 3 | 2007 | 22 | |
| 4 | 2015 | 17 | |
| 5 | 2009 | 16 | |
| 6 | 2005 | 6 | |
| 7 | 2020 | 4 | |
| 8 | 2020 | 1 |
About M. Lam
M. Lam is a scholar working on Molecular Biology, Epidemiology, Psychiatry and Mental health, Pathology and Forensic Medicine and Health, having authored 8 papers that have together received 628 indexed citations. Recurring topics across this work include Diabetes, Cardiovascular Risks, and Lipoproteins (1 paper), Machine Learning in Bioinformatics (1 paper), Long-Term Effects of COVID-19 (1 paper), Biochemical and Structural Characterization (1 paper), Alcohol Consumption and Health Effects (1 paper), Emergency and Acute Care Studies (1 paper), Bipolar Disorder and Treatment (1 paper) and Genomics and Phylogenetic Studies (1 paper). The work is most often cited by research in Neurology (396 citations), Critical Care and Intensive Care Medicine (82 citations), Clinical Psychology (331 citations), Biological Psychiatry (29 citations) and Psychiatry and Mental health (133 citations). M. Lam has collaborated with scholars based in Hong Kong, China and United States. Frequent co-authors include Yun Kwok Wing, Steven Wai Ho Chau, Adam Zemła, Hairong Nan, Linong Ji, Rose Z.W. Ting, Roseanne O. Yeung, Juliana C.N. Chan, Jianping Weng and Wenying Yang. Their work appears in journals such as Canadian Journal of Cardiology, Journal of Affective Disorders, General Hospital Psychiatry, Nucleic Acids Research and PLoS ONE.
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.