Mukesh G. Harisinghani
- Surgery top 0.5%
- Pulmonary and Respiratory Medicine top 0.5%
- Radiology, Nuclear Medicine and Imaging top 0.5%
- Biomedical Engineering top 2%
- Molecular Biology top 10%
- Co-authors
- Peter F. HahnRalph WeisslederPeter R. MüellerShahin TabatabaeiJelle O. BarentszWillem M. L. L. G. DesernoJean de la RosetteKartik Jhaveri
- Topics
- MRI in cancer diagnosis (51 papers)Radiomics and Machine Learning in Medical Imaging (51 papers)Prostate Cancer Diagnosis and Treatment (50 papers)
- Journals
- New England Journal of MedicineProceedings of the National Academy of SciencesJournal of Clinical Investigation
- Partner nations
- United StatesCanadaThailand
In The Last Decade
Mukesh G. Harisinghani
249 papers receiving 8.3k citations
Hit Papers
Peers
Comparison fields: 5 of 154
- Surgery 3.1k
- Pulmonary and Respiratory Medicine 2.7k
- Radiology, Nuclear Medicine and Imaging 2.5k
- Biomedical Engineering 1.2k
- Molecular Biology 936
Countries citing papers authored by Mukesh G. Harisinghani
This map shows the geographic impact of Mukesh G. Harisinghani'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 Mukesh G. Harisinghani with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mukesh G. Harisinghani more than expected).
Fields of papers citing papers by Mukesh G. Harisinghani
This network shows the impact of papers produced by Mukesh G. Harisinghani. 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 Mukesh G. Harisinghani. The network helps show where Mukesh G. Harisinghani may publish in the future.
Co-authorship network of co-authors of Mukesh G. Harisinghani
This figure shows the co-authorship network connecting the top 25 collaborators of Mukesh G. Harisinghani. A scholar is included among the top collaborators of Mukesh G. Harisinghani 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 Mukesh G. Harisinghani. Mukesh G. Harisinghani 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 | 0 | |
| 3 | 0 | |
| 4 | 3 | |
| 5 | 2 | |
| 6 | 6 | |
| 7 | 3 | |
| 8 | 59 | |
| 9 | 5 | |
| 10 | 100 | |
| 11 | 6 | |
| 12 | 9 | |
| 13 | 17 | |
| 14 | 8 | |
| 15 | 18 | |
| 16 | 10 | |
| 17 | 10 | |
| 18 | 62 | |
| 19 | 52 | |
| 20 | 4 |
About Mukesh G. Harisinghani
Mukesh G. Harisinghani is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Rheumatology, having authored 271 papers that have together received 8.5k indexed citations. Recurring topics across this work include MRI in cancer diagnosis (51 papers), Radiomics and Machine Learning in Medical Imaging (51 papers) and Prostate Cancer Diagnosis and Treatment (50 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (2.5k citations), Pulmonary and Respiratory Medicine (2.7k citations) and Surgery (3.1k citations). Mukesh G. Harisinghani has collaborated with scholars based in United States, Canada and Thailand. Frequent co-authors include Peter F. Hahn, Ralph Weissleder, Peter R. Müeller, Shahin Tabatabaei, Jelle O. Barentsz, Willem M. L. L. G. Deserno, Jean de la Rosette, Kartik Jhaveri, Sandeep Hedgire and Mansi A. Saksena. Their work appears in journals such as New England Journal of Medicine, Proceedings of the National Academy of Sciences and Journal of Clinical Investigation.
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.