Rohit Lamba
Impact in
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- Artificial Intelligence in Healthcare
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- Parkinson's Disease Mechanisms and Treatments
- Neurological disorders and treatments
- Brain Tumor Detection and Classification
Papers in
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- Artificial Intelligence in Healthcare 7
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- Imbalanced Data Classification Techniques 2
- Machine Learning in Healthcare 2
- AI in cancer detection 2
- Co-authors
- Anurag Jain (11 shared papers)Tarun Gulati (7 shared papers)Hadeel Alharbi (1 shared paper)Pooja Rani (11 shared papers)Ravi Kumar Sachdeva (9 shared papers)Kawther A. Al‐Dhlan (1 shared paper)Rajneesh Kumar (3 shared papers)Manoj Kumar (1 shared paper)
- Journals
- Arabian Journal for Science and Engineering (2 papers)Archives of Computational Methods in Engineering (1 paper)Neural Computing and Applications (1 paper)Journal of Reliable Intelligent Environments (1 paper)International Journal of Speech Technology (1 paper)
- Partner nations
- IndiaSaudi ArabiaUnited States
In The Last Decade
Rohit Lamba
16 papers receiving 282 citations
Peers
Comparison fields: 5 of 60
- Health Information Management 65
- Neurology 69
- Physiology 110
- Neurology 24
- Signal Processing 32
Countries citing papers authored by Rohit Lamba
This map shows the geographic impact of Rohit Lamba'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 Rohit Lamba with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rohit Lamba more than expected).
Fields of papers citing papers by Rohit Lamba
This network shows the impact of papers produced by Rohit Lamba. 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 Rohit Lamba. The network helps show where Rohit Lamba may publish in the future.
Co-authors
The 20 scholars most cited alongside Rohit Lamba, 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 | 2021 | 89 | |
| 2 | 2021 | 40 | |
| 3 | 2022 | 37 | |
| 4 | 2024 | 28 | |
| 5 | 2022 | 18 | |
| 6 | 2024 | 16 | |
| 7 | 2022 | 12 | |
| 8 | 2020 | 12 | |
| 9 | 2020 | 11 | |
| 10 | 2023 | 8 | |
| 11 | 2023 | 6 | |
| 12 | 2024 | 4 | |
| 13 | 2025 | 3 | |
| 14 | RECOGNIZING VOICE FOR NUMERICS USING MFCC AND DTW | 2013 | 3 |
| 15 | 2022 | 2 | |
| 16 | 2023 | 1 | |
| 17 | 2023 | 0 | |
| 18 | 2024 | 0 |
About Rohit Lamba
Rohit Lamba is a scholar working on Health Information Management, Artificial Intelligence, Physiology, Neurology and Neurology, having authored 18 papers that have together received 290 indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare (7 papers), Voice and Speech Disorders (5 papers), Brain Tumor Detection and Classification (3 papers), Parkinson's Disease Mechanisms and Treatments (3 papers), Imbalanced Data Classification Techniques (2 papers), Machine Learning in Healthcare (2 papers), AI in cancer detection (2 papers) and Electricity Theft Detection Techniques (1 paper). The work is most often cited by research in Health Information Management (65 citations), Neurology (69 citations), Physiology (110 citations), Neurology (24 citations) and Signal Processing (32 citations). Rohit Lamba has collaborated with scholars based in India, Saudi Arabia and United States. Frequent co-authors include Anurag Jain, Tarun Gulati, Hadeel Alharbi, Pooja Rani, Ravi Kumar Sachdeva, Kawther A. Al‐Dhlan, Rajneesh Kumar, Manoj Kumar, Celestine Iwendi and Arwa N. Aledaily. Their work appears in journals such as Arabian Journal for Science and Engineering, Archives of Computational Methods in Engineering, Neural Computing and Applications, Journal of Reliable Intelligent Environments and International Journal of Speech Technology.
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.