S. S. Vinod Chandra
- Health Informatics top 10%
- Software top 10%
- Artificial Intelligence top 5%
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- Advanced Optical Network Technologies 16
- Optical Network Technologies 12
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- Organ Transplantation Techniques and Outcomes 10
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- Liver Disease Diagnosis and Treatment 9
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- COVID-19 diagnosis using AI 8
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- MicroRNA in disease regulation 8
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- Liver Disease and Transplantation 8
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- Smart Agriculture and AI 7
- Co-authors
- Dinesh O. ShahE. ShajiG. ReshmiAchuthsankar S. NairJames R. LarusS. UshakumariRadhakrishna PillaiA. L. Achu
- Journals
- SHILAP Revista de lepidopterología (1 paper)Scientific Reports (2 papers)The FASEB Journal (1 paper)
- Partner nations
- IndiaUnited StatesIraq
In The Last Decade
S. S. Vinod Chandra
109 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 145
- Health Informatics 19
- Management, Monitoring, Policy and Law 113
- Health Information Management 42
- Software 29
- Artificial Intelligence 241
Countries citing papers authored by S. S. Vinod Chandra
This map shows the geographic impact of S. S. Vinod Chandra'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 S. S. Vinod Chandra with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites S. S. Vinod Chandra more than expected).
Fields of papers citing papers by S. S. Vinod Chandra
This network shows the impact of papers produced by S. S. Vinod Chandra. 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 S. S. Vinod Chandra. The network helps show where S. S. Vinod Chandra may publish in the future.
Co-authorship network
The 25 scholars most cited alongside S. S. Vinod Chandra, 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 | 2026 | 0 | |
| 2 | 2025 | 3 | |
| 3 | 2025 | 0 | |
| 4 | 2025 | 0 | |
| 5 | Precision farming for sustainability: An agricultural intelligence modelbreakdown → | 2024 | 52 |
| 6 | 2024 | 4 | |
| 7 | 2024 | 0 | |
| 8 | 2024 | 6 | |
| 9 | 2024 | 1 | |
| 10 | 2024 | 3 | |
| 11 | 2023 | 6 | |
| 12 | 2023 | 6 | |
| 13 | 2023 | 67 | |
| 14 | 2023 | 7 | |
| 15 | 2021 | 1 | |
| 16 | 2021 | 11 | |
| 17 | 2011 | 15 | |
| 18 | HEADWAY MODELLING UNDER MIXED TRAFFIC ON URBAN ROADS | 2001 | 11 |
| 19 | EFFECT OF DIRECTIONAL SPLIT AND SLOW-MOVING VEHICLES ON TWO LANE CAPACITY | 2001 | 7 |
| 20 | 1970 | 8 |
About S. S. Vinod Chandra
S. S. Vinod Chandra is a scholar working on Health Information Management, Software and Hepatology, having authored 122 papers that have together received 1.2k indexed citations. Recurring topics across this work include Advanced Optical Network Technologies (16 papers), Optical Network Technologies (12 papers), Organ Transplantation Techniques and Outcomes (10 papers), Liver Disease Diagnosis and Treatment (9 papers), COVID-19 diagnosis using AI (8 papers), MicroRNA in disease regulation (8 papers), Liver Disease and Transplantation (8 papers) and Smart Agriculture and AI (7 papers). The work is most often cited by research in Health Informatics (19 citations), Management, Monitoring, Policy and Law (113 citations) and Health Information Management (42 citations). S. S. Vinod Chandra has collaborated with scholars based in India, United States and Iraq. Frequent co-authors include Dinesh O. Shah, E. Shaji, G. Reshmi, Achuthsankar S. Nair, James R. Larus, S. Ushakumari, Radhakrishna Pillai, A. L. Achu, Mariano Di Napoli and Girish Gopinath. Their work appears in journals such as SHILAP Revista de lepidopterología, Scientific Reports and The FASEB Journal.
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.