Jay Acharya
Impact in
- Genetics top 5%
- Glioma Diagnosis and Treatment
- Hemoglobinopathies and Related Disorders
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- Radiomics and Machine Learning in Medical Imaging
- MRI in cancer diagnosis
Papers in
-
- Advanced MRI Techniques and Applications 4
- Radiology practices and education 4
- MRI in cancer diagnosis 4
- COVID-19 diagnosis using AI 3
- Radiation Dose and Imaging 3
- Surgery 12
- Co-authors
- Anandh Rajamohan (12 shared papers)Thomas C. Pearson (4 shared papers)Paul E. Kim (5 shared papers)Vishal Patel (8 shared papers)Krishna S. Nayak (5 shared papers)John L. Go (5 shared papers)Mark S. Shiroishi (2 shared papers)Judith Taylor (2 shared papers)
- Journals
- American Journal of Neuroradiology (5 papers)British Journal of Haematology (2 papers)Magnetic Resonance in Medicine (2 papers)Academic Radiology (2 papers)American Journal of Roentgenology (2 papers)
- Partner nations
- United StatesUnited KingdomCanada
In The Last Decade
Jay Acharya
47 papers receiving 812 citations
Peers
Comparison fields: 5 of 106
- Genetics 176
- Radiology, Nuclear Medicine and Imaging 234
- Health Informatics 13
- Hematology 74
- Neurology 44
Countries citing papers authored by Jay Acharya
This map shows the geographic impact of Jay Acharya'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 Jay Acharya with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jay Acharya more than expected).
Fields of papers citing papers by Jay Acharya
This network shows the impact of papers produced by Jay Acharya. 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 Jay Acharya. The network helps show where Jay Acharya may publish in the future.
Co-authors
The 25 scholars most cited alongside Jay Acharya, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 51 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 112 | |
| 2 | 2013 | 83 | |
| 3 | 2005 | 71 | |
| 4 | 2020 | 68 | |
| 5 | 2020 | 66 | |
| 6 | 1991 | 55 | |
| 7 | 2020 | 47 | |
| 8 | 1998 | 39 | |
| 9 | 2015 | 29 | |
| 10 | 2008 | 24 | |
| 11 | 2019 | 21 | |
| 12 | 2018 | 19 | |
| 13 | 2020 | 19 | |
| 14 | 1989 | 18 | |
| 15 | 1995 | 15 | |
| 16 | 2017 | 14 | |
| 17 | 2014 | 12 | |
| 18 | 2013 | 12 | |
| 19 | 2020 | 10 | |
| 20 | 2012 | 9 |
About Jay Acharya
Jay Acharya is a scholar working on Radiology, Nuclear Medicine and Imaging, Surgery, Genetics, Neurology and Pulmonary and Respiratory Medicine, having authored 51 papers that have together received 832 indexed citations. Recurring topics across this work include Advanced MRI Techniques and Applications (4 papers), Radiology practices and education (4 papers), MRI in cancer diagnosis (4 papers), Myeloproliferative Neoplasms: Diagnosis and Treatment (3 papers), COVID-19 diagnosis using AI (3 papers), Radiation Dose and Imaging (3 papers), Meningioma and schwannoma management (3 papers) and Glioma Diagnosis and Treatment (3 papers). The work is most often cited by research in Genetics (176 citations), Radiology, Nuclear Medicine and Imaging (234 citations), Health Informatics (13 citations), Hematology (74 citations) and Neurology (44 citations). Jay Acharya has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Anandh Rajamohan, Thomas C. Pearson, Paul E. Kim, Vishal Patel, Krishna S. Nayak, John L. Go, Mark S. Shiroishi, Judith Taylor, Nasim Sheikh‐Bahaei and Neville A Punchard. Their work appears in journals such as American Journal of Neuroradiology, British Journal of Haematology, Magnetic Resonance in Medicine, Academic Radiology 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.