Ziyad Al‐Aly
- Neurology top 0.2%
- Infectious Diseases top 0.5%
- Nephrology top 0.2%
- Health, Toxicology and Mutagenesis top 0.5%
- Clinical Psychology top 1%
- Topics
- Long-Term Effects of COVID-19 (29 papers)COVID-19 Clinical Research Studies (27 papers)Chronic Kidney Disease and Diabetes (20 papers)
- Partner nations
- United StatesCanadaSouth Africa
In The Last Decade
Ziyad Al‐Aly
105 papers receiving 10.4k citations
Hit Papers
Peers
Comparison fields: 5 of 177
- Neurology 3.3k
- Infectious Diseases 2.8k
- Nephrology 1.8k
- Health, Toxicology and Mutagenesis 1.3k
- Clinical Psychology 1.2k
Countries citing papers authored by Ziyad Al‐Aly
This map shows the geographic impact of Ziyad Al‐Aly'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 Ziyad Al‐Aly with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ziyad Al‐Aly more than expected).
Fields of papers citing papers by Ziyad Al‐Aly
This network shows the impact of papers produced by Ziyad Al‐Aly. 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 Ziyad Al‐Aly. The network helps show where Ziyad Al‐Aly may publish in the future.
Co-authorship network of co-authors of Ziyad Al‐Aly
This figure shows the co-authorship network connecting the top 25 collaborators of Ziyad Al‐Aly. A scholar is included among the top collaborators of Ziyad Al‐Aly 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 Ziyad Al‐Aly. Ziyad Al‐Aly is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 6 | |
| 2 | Mapping the effectiveness and risks of GLP-1 receptor agonistsbreakdown → | 98 |
| 3 | 64 | |
| 4 | Association of Treatment With Nirmatrelvir and the Risk of Post–COVID-19 Conditionbreakdown → | 184 |
| 5 | 29 | |
| 6 | Long-term outcomes following hospital admission for COVID-19 versus seasonal influenza: a cohort studybreakdown → | 73 |
| 7 | 31 | |
| 8 | 6 | |
| 9 | 24 | |
| 10 | 38 | |
| 11 | High-dimensional characterization of post-acute sequelae of COVID-19breakdown → | 876 |
| 12 | 41 | |
| 13 | 66 | |
| 14 | 176 | |
| 15 | 154 | |
| 16 | 238 | |
| 17 | 46 | |
| 18 | 10 | |
| 19 | 2 | |
| 20 | 31 |
About Ziyad Al‐Aly
Ziyad Al‐Aly is a scholar working on Nephrology, Critical Care and Intensive Care Medicine and Neurology, having authored 109 papers that have together received 10.6k indexed citations. Recurring topics across this work include Long-Term Effects of COVID-19 (29 papers), COVID-19 Clinical Research Studies (27 papers) and Chronic Kidney Disease and Diabetes (20 papers). The work is most often cited by research in Nephrology (1.8k citations), Neurology (3.3k citations) and Critical Care and Intensive Care Medicine (923 citations). Ziyad Al‐Aly has collaborated with scholars based in United States, Canada and South Africa. Frequent co-authors include Yan Xie, Benjamin Bowe, Hong Xian, Evan Xu, Tingting Li, Yan Yan, Geetha Maddukuri, Taeyoung Choi, Sumitra Balasubramanian and Ali H. Mokdad. Their work appears in journals such as Nature, Science and New England Journal of Medicine.
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.