Paras Lakhani
- Radiology, Nuclear Medicine and Imaging top 1%
- Artificial Intelligence top 2%
- Pulmonary and Respiratory Medicine top 5%
- Health Informatics top 0.2%
- Biomedical Engineering top 10%
- Co-authors
- Baskaran SundaramCurtis P. LanglotzAdam E. FlandersAbass AlaviHongming ZhuangGeorge ShihPaul NagyRichard Gorniak
- Topics
- Radiomics and Machine Learning in Medical Imaging (9 papers)Radiology practices and education (9 papers)COVID-19 diagnosis using AI (7 papers)
- Journals
- RadiologyInternational Journal of Radiation Oncology*Biology*PhysicsAmerican Journal of Roentgenology
- Partner nations
- United StatesJapanAustralia
In The Last Decade
Paras Lakhani
37 papers receiving 1.9k citations
Hit Papers
Peers
Comparison fields: 5 of 134
- Radiology, Nuclear Medicine and Imaging 1.3k
- Artificial Intelligence 517
- Pulmonary and Respiratory Medicine 498
- Health Informatics 343
- Biomedical Engineering 255
Countries citing papers authored by Paras Lakhani
This map shows the geographic impact of Paras Lakhani'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 Paras Lakhani with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Paras Lakhani more than expected).
Fields of papers citing papers by Paras Lakhani
This network shows the impact of papers produced by Paras Lakhani. 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 Paras Lakhani. The network helps show where Paras Lakhani may publish in the future.
Co-authorship network of co-authors of Paras Lakhani
This figure shows the co-authorship network connecting the top 25 collaborators of Paras Lakhani. A scholar is included among the top collaborators of Paras Lakhani 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 Paras Lakhani. Paras Lakhani 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 | 6 | |
| 3 | 17 | |
| 4 | 8 | |
| 5 | 76 | |
| 6 | 41 | |
| 7 | 167 | |
| 8 | 19 | |
| 9 | 46 | |
| 10 | 1 | |
| 11 | 3 | |
| 12 | 8 | |
| 13 | 4 | |
| 14 | 20 | |
| 15 | 15 | |
| 16 | 12 | |
| 17 | 22 | |
| 18 | 9 | |
| 19 | 42 | |
| 20 | 33 |
About Paras Lakhani
Paras Lakhani is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine, having authored 39 papers that have together received 2.0k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (9 papers), Radiology practices and education (9 papers) and COVID-19 diagnosis using AI (7 papers). The work is most often cited by research in Health Informatics (343 citations), Radiology, Nuclear Medicine and Imaging (1.3k citations) and Health Information Management (75 citations). Paras Lakhani has collaborated with scholars based in United States, Japan and Australia. Frequent co-authors include Baskaran Sundaram, Curtis P. Langlotz, Adam E. Flanders, Abass Alavi, Hongming Zhuang, George Shih, Paul Nagy, Richard Gorniak, Ayşe Mavi and Jason N. Itri. Their work appears in journals such as Radiology, International Journal of Radiation Oncology*Biology*Physics and American Journal of Roentgenology.
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.