Suddhasatta Acharyya
- Pulmonary and Respiratory Medicine top 1%
- Oncology top 2%
- Artificial Intelligence top 1%
- Radiology, Nuclear Medicine and Imaging top 1%
- Cancer Research top 5%
- Co-authors
- Etta D. PisanoConstantine GatsonisMartin J. YaffeEmily F. ConantJanet K. BaumLawrence W. BassettRoberta A. JongMurray Rebner
- Topics
- AI in cancer detection (9 papers)Digital Radiography and Breast Imaging (9 papers)Chronic Myeloid Leukemia Treatments (8 papers)
- Partner nations
- United StatesSwitzerlandGermany
In The Last Decade
Suddhasatta Acharyya
33 papers receiving 3.2k citations
Hit Papers
Peers
Comparison fields: 5 of 124
- Pulmonary and Respiratory Medicine 1.5k
- Oncology 1.2k
- Artificial Intelligence 1.2k
- Radiology, Nuclear Medicine and Imaging 910
- Cancer Research 453
Countries citing papers authored by Suddhasatta Acharyya
This map shows the geographic impact of Suddhasatta Acharyya'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 Suddhasatta Acharyya with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Suddhasatta Acharyya more than expected).
Fields of papers citing papers by Suddhasatta Acharyya
This network shows the impact of papers produced by Suddhasatta Acharyya. 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 Suddhasatta Acharyya. The network helps show where Suddhasatta Acharyya may publish in the future.
Co-authorship network of co-authors of Suddhasatta Acharyya
This figure shows the co-authorship network connecting the top 25 collaborators of Suddhasatta Acharyya. A scholar is included among the top collaborators of Suddhasatta Acharyya 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 Suddhasatta Acharyya. Suddhasatta Acharyya is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 94 | |
| 3 | 4 | |
| 4 | 2 | |
| 5 | 1 | |
| 6 | 5 | |
| 7 | 31 | |
| 8 | 5 | |
| 9 | 48 | |
| 10 | 58 | |
| 11 | 55 | |
| 12 | 14 | |
| 13 | 16 | |
| 14 | 324 | |
| 15 | 26 | |
| 16 | 408 | |
| 17 | Diagnostic Performance of Digital versus Film Mammography for Breast-Cancer Screeningbreakdown → | 1331 |
| 18 | 36 | |
| 19 | 341 | |
| 20 | 121 |
About Suddhasatta Acharyya
Suddhasatta Acharyya is a scholar working on Hematology, Genetics and Oncology, having authored 33 papers that have together received 3.3k indexed citations. Recurring topics across this work include AI in cancer detection (9 papers), Digital Radiography and Breast Imaging (9 papers) and Chronic Myeloid Leukemia Treatments (8 papers). The work is most often cited by research in Oncology (1.2k citations), Pulmonary and Respiratory Medicine (1.5k citations) and Radiology, Nuclear Medicine and Imaging (910 citations). Suddhasatta Acharyya has collaborated with scholars based in United States, Switzerland and Germany. Frequent co-authors include Etta D. Pisano, Constantine Gatsonis, Martin J. Yaffe, Emily F. Conant, Janet K. Baum, Lawrence W. Bassett, Roberta A. Jong, Murray Rebner, Laurie L. Fajardo and Edward Hendrick. Their work appears in journals such as New England Journal of Medicine, Journal of Clinical Oncology and Blood.
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.