Dolly Das
Impact in
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- Artificial Intelligence in Healthcare
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- Retinal Imaging and Analysis
- COVID-19 diagnosis using AI
Papers in
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- Retinal Imaging and Analysis 9
- COVID-19 diagnosis using AI 4
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- Artificial Intelligence in Healthcare 6
- Co-authors
- Saroj Kr. Biswas (15 shared papers)Sivaji Bandyopadhyay (6 shared papers)Biswajit Purkayastha (9 shared papers)Alexandre E. Escargueil (1 shared paper)Ankit Kesharwani (1 shared paper)Manomita Chakraborty (4 shared papers)Rahul Barman (1 shared paper)Malaya Dutta Borah (1 shared paper)
- Journals
- Multimedia Tools and Applications (4 papers)International Journal of Imaging Systems and Technology (1 paper)Journal of Indian Business Research (1 paper)Lecture notes in electrical engineering (1 paper)Advances in intelligent systems and computing (1 paper)
In The Last Decade
Dolly Das
19 papers receiving 352 citations
Peers
Comparison fields: 5 of 83
- Health Information Management 99
- Radiology, Nuclear Medicine and Imaging 213
- Ophthalmology 69
- Health Informatics 8
- Neurology 36
Countries citing papers authored by Dolly Das
This map shows the geographic impact of Dolly Das'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 Dolly Das with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dolly Das more than expected).
Fields of papers citing papers by Dolly Das
This network shows the impact of papers produced by Dolly Das. 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 Dolly Das. The network helps show where Dolly Das may publish in the future.
Co-authors
The 12 scholars most cited alongside Dolly Das, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 92 | |
| 2 | 2023 | 83 | |
| 3 | 2022 | 81 | |
| 4 | 2016 | 40 | |
| 5 | 2022 | 19 | |
| 6 | 2022 | 17 | |
| 7 | 2022 | 17 | |
| 8 | 2022 | 5 | |
| 9 | 2023 | 5 | |
| 10 | 2021 | 3 | |
| 11 | 2016 | 3 | |
| 12 | 2021 | 3 | |
| 13 | 2021 | 2 | |
| 14 | 2020 | 2 | |
| 15 | 2020 | 2 | |
| 16 | 2020 | 2 | |
| 17 | 2021 | 1 | |
| 18 | 2023 | 1 | |
| 19 | A Differential Evolutionary Approach to Solve the Hardware Software Partitioning Problem | 2014 | 1 |
About Dolly Das
Dolly Das is a scholar working on Radiology, Nuclear Medicine and Imaging, Health Information Management, Ophthalmology, Computer Vision and Pattern Recognition and Health Informatics, having authored 19 papers that have together received 379 indexed citations. Recurring topics across this work include Retinal Imaging and Analysis (9 papers), Digital Imaging for Blood Diseases (6 papers), Artificial Intelligence in Healthcare (6 papers), Retinal Diseases and Treatments (6 papers), COVID-19 diagnosis using AI (4 papers), AI in cancer detection (2 papers), Real-Time Systems Scheduling (1 paper) and COVID-19 Clinical Research Studies (1 paper). The work is most often cited by research in Health Information Management (99 citations), Radiology, Nuclear Medicine and Imaging (213 citations), Ophthalmology (69 citations), Health Informatics (8 citations) and Neurology (36 citations). Dolly Das has collaborated with scholars based in India and France. Frequent co-authors include Saroj Kr. Biswas, Sivaji Bandyopadhyay, Biswajit Purkayastha, Alexandre E. Escargueil, Ankit Kesharwani, Manomita Chakraborty, Rahul Barman, Malaya Dutta Borah, Rabul Hussain Laskar and Sunita Sarkar. Their work appears in journals such as Multimedia Tools and Applications, International Journal of Imaging Systems and Technology, Journal of Indian Business Research, Lecture notes in electrical engineering and Advances in intelligent systems and computing.
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.