Keerthana Prasad
- Biophysics top 2%
- Cell Image Analysis Techniques 10
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- Digital Imaging for Blood Diseases 22
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- Radiomics and Machine Learning in Medical Imaging 9
- Infrared Thermography in Medicine 8
- Artificial Intelligence top 2%
- AI in cancer detection 30
- Health Informatics top 10%
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- Cervical Cancer and HPV Research 7
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- Smart Agriculture and AI 6
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- Dermatologic Treatments and Research 5
- Co-authors
- Roopa B. HegdeHarishchandra HebbarBrij Mohan Kumar SinghK. Gopalakrishna PrabhuShyamala GuruvareSurekha KamathRajagopal KadavigerePramod Kumar
- Journals
- SHILAP Revista de lepidopterología (1 paper)PLoS ONE (1 paper)IEEE Access (1 paper)
In The Last Decade
Keerthana Prasad
69 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 137
- Biophysics 152
- Computer Vision and Pattern Recognition 512
- Radiology, Nuclear Medicine and Imaging 489
- Artificial Intelligence 516
- Health Informatics 21
Countries citing papers authored by Keerthana Prasad
This map shows the geographic impact of Keerthana Prasad'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 Keerthana Prasad with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Keerthana Prasad more than expected).
Fields of papers citing papers by Keerthana Prasad
This network shows the impact of papers produced by Keerthana Prasad. 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 Keerthana Prasad. The network helps show where Keerthana Prasad may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Keerthana Prasad, 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 | 2025 | 0 | |
| 2 | 2024 | 4 | |
| 3 | 2024 | 0 | |
| 4 | 2023 | 10 | |
| 5 | 2023 | 4 | |
| 6 | 2022 | 11 | |
| 7 | 2022 | 40 | |
| 8 | 2021 | 5 | |
| 9 | 2019 | 46 | |
| 10 | 2018 | 9 | |
| 11 | BIOMECHANICAL, BIOCHEMICAL AND HISTOLOGICAL EVIDENCES FOR WOUND HEALING PROPERTIES OF INDIAN TRADITIONAL MEDICINES | 2015 | 9 |
| 12 | 2014 | 9 | |
| 13 | Morphometric Evaluation of Anterior Fontanelle: A Fetal Cadaveric Study | 2014 | 1 |
| 14 | 2014 | 9 | |
| 15 | 2012 | 11 | |
| 16 | 2011 | 23 | |
| 17 | 2011 | 9 | |
| 18 | 2011 | 4 | |
| 19 | 2010 | 8 | |
| 20 | 2009 | 50 |
About Keerthana Prasad
Keerthana Prasad is a scholar working on Biophysics, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition, having authored 74 papers that have together received 1.3k indexed citations. Recurring topics across this work include AI in cancer detection (30 papers), Digital Imaging for Blood Diseases (22 papers), Cell Image Analysis Techniques (10 papers), Radiomics and Machine Learning in Medical Imaging (9 papers), Infrared Thermography in Medicine (8 papers), Cervical Cancer and HPV Research (7 papers), Smart Agriculture and AI (6 papers) and Dermatologic Treatments and Research (5 papers). The work is most often cited by research in Biophysics (152 citations), Computer Vision and Pattern Recognition (512 citations) and Radiology, Nuclear Medicine and Imaging (489 citations). Keerthana Prasad has collaborated with scholars based in India, Australia and Uganda. Frequent co-authors include Roopa B. Hegde, Harishchandra Hebbar, Brij Mohan Kumar Singh, K. Gopalakrishna Prabhu, Shyamala Guruvare, Surekha Kamath, Rajagopal Kadavigere, Pramod Kumar, Brij Mohan Kumar Singh and Roshan Joy Martis. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and IEEE Access.
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.