Tripti Goel
Impact in
- Neurology top 2%
- Brain Tumor Detection and Classification
- Health Informatics top 5%
Papers in
- Neurology 28
- Brain Tumor Detection and Classification 28
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- Retinal Imaging and Analysis 22
- COVID-19 diagnosis using AI 12
- Radiomics and Machine Learning in Medical Imaging 9
- Co-authors
- R. Anandha Murugan (66 shared papers)M. Tanveer (23 shared papers)Rahul Sharma (13 shared papers)Seyedali Mirjalili (7 shared papers)Chin‐Teng Lin (4 shared papers)Virendra Prasad Vishwakarma (8 shared papers)Ponnuthurai Nagaratnam Suganthan (5 shared papers)Vijay Nehra (7 shared papers)
- Journals
- Cognitive Computation (4 papers)Applied Soft Computing (4 papers)Biomedical Signal Processing and Control (4 papers)Information Fusion (3 papers)Multimedia Tools and Applications (3 papers)
- Partner nations
- IndiaAustraliaSouth Korea
In The Last Decade
Tripti Goel
89 papers receiving 1.4k citations
Tripti Goel's Hit Papers
Peers
Comparison fields: 5 of 102
- Neurology 334
- Health Informatics 48
- Health Information Management 137
- Radiology, Nuclear Medicine and Imaging 574
- Computer Vision and Pattern Recognition 387
Countries citing papers authored by Tripti Goel
This map shows the geographic impact of Tripti Goel'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 Tripti Goel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tripti Goel more than expected).
Fields of papers citing papers by Tripti Goel
This network shows the impact of papers produced by Tripti Goel. 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 Tripti Goel. The network helps show where Tripti Goel may publish in the future.
Co-authors
The 25 scholars most cited alongside Tripti Goel, 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 93 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 136 | |
| 2 | Deep learning for brain age estimation: A systematic review Hit paper breakdown → | 2023 | 95 |
| 3 | 2021 | 76 | |
| 4 | 2022 | 71 | |
| 5 | 2021 | 62 | |
| 6 | 2021 | 56 | |
| 7 | 2023 | 55 | |
| 8 | 2021 | 50 | |
| 9 | 2023 | 44 | |
| 10 | 2024 | 40 | |
| 11 | 2021 | 38 | |
| 12 | 2022 | 36 | |
| 13 | 2023 | 33 | |
| 14 | 2022 | 30 | |
| 15 | 2023 | 30 | |
| 16 | 2021 | 29 | |
| 17 | 2022 | 28 | |
| 18 | 2024 | 27 | |
| 19 | 2020 | 25 | |
| 20 | 2023 | 25 |
About Tripti Goel
Tripti Goel is a scholar working on Neurology, Radiology, Nuclear Medicine and Imaging, Ophthalmology, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 93 papers that have together received 1.4k indexed citations. Recurring topics across this work include Brain Tumor Detection and Classification (28 papers), Retinal Imaging and Analysis (22 papers), Retinal Diseases and Treatments (14 papers), COVID-19 diagnosis using AI (12 papers), Face and Expression Recognition (11 papers), Retinal and Optic Conditions (9 papers), Radiomics and Machine Learning in Medical Imaging (9 papers) and Functional Brain Connectivity Studies (9 papers). The work is most often cited by research in Neurology (334 citations), Health Informatics (48 citations), Health Information Management (137 citations), Radiology, Nuclear Medicine and Imaging (574 citations) and Computer Vision and Pattern Recognition (387 citations). Tripti Goel has collaborated with scholars based in India, Australia and South Korea. Frequent co-authors include R. Anandha Murugan, M. Tanveer, Rahul Sharma, Seyedali Mirjalili, Chin‐Teng Lin, Virendra Prasad Vishwakarma, Ponnuthurai Nagaratnam Suganthan, Vijay Nehra, Javier Del Ser and Y Zhang. Their work appears in journals such as Cognitive Computation, Applied Soft Computing, Biomedical Signal Processing and Control, Information Fusion and Multimedia Tools and Applications.
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.