Fnu Neha
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
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- Artificial Intelligence in Healthcare
Papers in
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- Machine Learning in Healthcare 5
- Topic Modeling 2
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- Radiomics and Machine Learning in Medical Imaging 5
- Co-authors
- Md Amiruzzaman (7 shared papers)Muhammad Saqib (3 shared papers)Hassan Mumtaz (3 shared papers)Muhammad Iftikhar (1 shared paper)Arvind K. Bansal (5 shared papers)Angela Guercio (4 shared papers)Satesh Kumar (2 shared papers)Mahima Khatri (2 shared papers)
- Journals
- Frontiers in Medicine (1 paper)Annals of Medicine and Surgery (1 paper)Journal of Imaging (1 paper)Journal of Clinical and Translational Science (1 paper)BioMedInformatics (1 paper)
- Partner nations
- United StatesPakistanItaly
In The Last Decade
Fnu Neha
22 papers receiving 167 citations
Peers
Comparison fields: 5 of 61
- Health Informatics 45
- Health Information Management 7
- Radiology, Nuclear Medicine and Imaging 26
- Artificial Intelligence 38
- Neurology 7
Countries citing papers authored by Fnu Neha
This map shows the geographic impact of Fnu Neha'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 Fnu Neha with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fnu Neha more than expected).
Fields of papers citing papers by Fnu Neha
This network shows the impact of papers produced by Fnu Neha. 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 Fnu Neha. The network helps show where Fnu Neha may publish in the future.
Co-authors
The 16 scholars most cited alongside Fnu Neha, 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 29 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 42 | |
| 2 | 2024 | 29 | |
| 3 | 2023 | 15 | |
| 4 | 2023 | 14 | |
| 5 | 2024 | 14 | |
| 6 | 2024 | 8 | |
| 7 | 2025 | 7 | |
| 8 | 2023 | 6 | |
| 9 | 2025 | 5 | |
| 10 | 2024 | 5 | |
| 11 | 2025 | 3 | |
| 12 | 2025 | 3 | |
| 13 | 2024 | 3 | |
| 14 | 2025 | 3 | |
| 15 | 2025 | 2 | |
| 16 | 2025 | 2 | |
| 17 | 2023 | 2 | |
| 18 | 2025 | 1 | |
| 19 | 2024 | 1 | |
| 20 | 2024 | 1 |
About Fnu Neha
Fnu Neha is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Health Informatics, Pulmonary and Respiratory Medicine and Biomedical Engineering, having authored 29 papers that have together received 168 indexed citations. Recurring topics across this work include Machine Learning in Healthcare (5 papers), Radiomics and Machine Learning in Medical Imaging (5 papers), Artificial Intelligence in Healthcare and Education (4 papers), Renal cell carcinoma treatment (2 papers), Advanced X-ray and CT Imaging (2 papers), Brain Tumor Detection and Classification (2 papers), Diabetes Treatment and Management (2 papers) and Topic Modeling (2 papers). The work is most often cited by research in Health Informatics (45 citations), Health Information Management (7 citations), Radiology, Nuclear Medicine and Imaging (26 citations), Artificial Intelligence (38 citations) and Neurology (7 citations). Fnu Neha has collaborated with scholars based in United States, Pakistan and Italy. Frequent co-authors include Md Amiruzzaman, Muhammad Saqib, Hassan Mumtaz, Muhammad Iftikhar, Arvind K. Bansal, Angela Guercio, Satesh Kumar, Mahima Khatri, Giustino Varrassi and Shehroze Tabassum. Their work appears in journals such as Frontiers in Medicine, Annals of Medicine and Surgery, Journal of Imaging, Journal of Clinical and Translational Science and BioMedInformatics.
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.