Sandeep Chaurasia
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- Artificial Intelligence in Healthcare 3
- Artificial Intelligence top 10%
- AI in cancer detection 5
- Sentiment Analysis and Opinion Mining 3
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- Radiomics and Machine Learning in Medical Imaging 3
- COVID-19 diagnosis using AI 3
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- Rheumatoid Arthritis Research and Therapies 3
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- Occupational Health and Safety Research 2
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- Hydrological Forecasting Using AI 2
- Co-authors
- Devesh Kumar SrivastavaPrąsun ChakrabartiVadim BolshevTulika ChakrabartiRadomír GoňoMichał JasińskiPankaj ChittoraZbigniew Leonowicz
- Journals
- Scientific Reports (1 paper)Engineering Applications of Artificial Intelligence (1 paper)IEEE Access (1 paper)
- Partner nations
- IndiaCzechiaSaudi Arabia
In The Last Decade
Sandeep Chaurasia
25 papers receiving 348 citations
Hit Papers
Peers
Comparison fields: 5 of 90
- Health Information Management 141
- Health Informatics 10
- Artificial Intelligence 171
- Radiology, Nuclear Medicine and Imaging 55
- Neurology 19
Countries citing papers authored by Sandeep Chaurasia
This map shows the geographic impact of Sandeep Chaurasia'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 Sandeep Chaurasia with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sandeep Chaurasia more than expected).
Fields of papers citing papers by Sandeep Chaurasia
This network shows the impact of papers produced by Sandeep Chaurasia. 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 Sandeep Chaurasia. The network helps show where Sandeep Chaurasia may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Sandeep Chaurasia, 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 | 2 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 2 | |
| 4 | 2024 | 2 | |
| 5 | 2024 | 1 | |
| 6 | 2024 | 6 | |
| 7 | 2024 | 0 | |
| 8 | 2023 | 2 | |
| 9 | 2022 | 1 | |
| 10 | 2022 | 37 | |
| 11 | Management of oral submucous fibrosis: A Review | 2021 | 8 |
| 12 | 2021 | 1 | |
| 13 | 2021 | 10 | |
| 14 | 2018 | 1 | |
| 15 | 2018 | 1 | |
| 16 | 2018 | 1 | |
| 17 | 2016 | 1 | |
| 18 | 2014 | 4 | |
| 19 | 2013 | 7 | |
| 20 | 2012 | 9 |
About Sandeep Chaurasia
Sandeep Chaurasia is a scholar working on Medical Laboratory Technology, Health Information Management and Artificial Intelligence, having authored 28 papers that have together received 378 indexed citations. Recurring topics across this work include AI in cancer detection (5 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), Sentiment Analysis and Opinion Mining (3 papers), Artificial Intelligence in Healthcare (3 papers), Rheumatoid Arthritis Research and Therapies (3 papers), COVID-19 diagnosis using AI (3 papers), Occupational Health and Safety Research (2 papers) and Hydrological Forecasting Using AI (2 papers). The work is most often cited by research in Health Information Management (141 citations), Health Informatics (10 citations) and Artificial Intelligence (171 citations). Sandeep Chaurasia has collaborated with scholars based in India, Czechia and Saudi Arabia. Frequent co-authors include Devesh Kumar Srivastava, Prąsun Chakrabarti, Vadim Bolshev, Tulika Chakrabarti, Radomír Goňo, Michał Jasiński, Pankaj Chittora, Zbigniew Leonowicz, Elżbieta Jasińska and Mahesh Jangid. Their work appears in journals such as Scientific Reports, Engineering Applications of Artificial Intelligence, IEEE Access, BMC Musculoskeletal Disorders and Biomedical Signal Processing and Control.
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.