Ashima Singh
Impact in
-
- Artificial Intelligence in Healthcare
- Health Informatics top 10%
Papers in ⓘ
-
- AI in cancer detection 5
-
- Software Engineering Research 7
- Co-authors
- A.P. Dhillon (9 shared papers)Parampreet Kaur (5 shared papers)Amrita Kaur (7 shared papers)Lakhwinder Kaur (4 shared papers)Inderveer Chana (3 shared papers)Sushma Jain (4 shared papers)Gitika Sharma (4 shared papers)Sukhpal Singh Gill (5 shared papers)
- Journals
- Neural Computing and Applications (4 papers)Archives of Computational Methods in Engineering (4 papers)Applied Soft Computing (2 papers)Multimedia Tools and Applications (2 papers)Scientific Reports (1 paper)
- Partner nations
- IndiaUnited KingdomCanada
In The Last Decade
Ashima Singh
47 papers receiving 738 citations
Peers
Comparison fields: 5 of 123
- Health Information Management 97
- Health Informatics 15
- Artificial Intelligence 227
- Computer Vision and Pattern Recognition 130
- Neurology 42
Countries citing papers authored by Ashima Singh
This map shows the geographic impact of Ashima Singh'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 Ashima Singh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ashima Singh more than expected).
Fields of papers citing papers by Ashima Singh
This network shows the impact of papers produced by Ashima Singh. 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 Ashima Singh. The network helps show where Ashima Singh may publish in the future.
Co-authors
The 25 scholars most cited alongside Ashima Singh, 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 57 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 54 | |
| 2 | Machine Learning in Healthcare Data Analysis: A Survey | 2019 | 48 |
| 3 | 2020 | 46 | |
| 4 | 2021 | 46 | |
| 5 | 2022 | 45 | |
| 6 | 2021 | 42 | |
| 7 | 2021 | 36 | |
| 8 | 2004 | 35 | |
| 9 | 2010 | 31 | |
| 10 | 2021 | 30 | |
| 11 | 2019 | 28 | |
| 12 | 2018 | 28 | |
| 13 | 2020 | 27 | |
| 14 | 2020 | 25 | |
| 15 | 2020 | 25 | |
| 16 | 2022 | 23 | |
| 17 | 2022 | 23 | |
| 18 | 2020 | 22 | |
| 19 | 2019 | 21 | |
| 20 | 2016 | 19 |
About Ashima Singh
Ashima Singh is a scholar working on Artificial Intelligence, Information Systems, Computer Networks and Communications, Molecular Biology and Radiology, Nuclear Medicine and Imaging, having authored 57 papers that have together received 778 indexed citations. Recurring topics across this work include Software Engineering Research (7 papers), Gene expression and cancer classification (7 papers), Artificial Intelligence in Healthcare (6 papers), AI in cancer detection (5 papers), Bioinformatics and Genomic Networks (5 papers), Radiomics and Machine Learning in Medical Imaging (5 papers), COVID-19 diagnosis using AI (4 papers) and Advanced Battery Technologies Research (4 papers). The work is most often cited by research in Health Information Management (97 citations), Health Informatics (15 citations), Artificial Intelligence (227 citations), Computer Vision and Pattern Recognition (130 citations) and Neurology (42 citations). Ashima Singh has collaborated with scholars based in India, United Kingdom and Canada. Frequent co-authors include A.P. Dhillon, Parampreet Kaur, Amrita Kaur, Lakhwinder Kaur, Inderveer Chana, Sushma Jain, Gitika Sharma, Sukhpal Singh Gill, Vinod K. Bhalla and Mahesh K. Singh. Their work appears in journals such as Neural Computing and Applications, Archives of Computational Methods in Engineering, Applied Soft Computing, Multimedia Tools and Applications and Scientific Reports.
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.