Rohit Lamba
Impact in
-
- Artificial Intelligence in Healthcare
-
- Parkinson's Disease Mechanisms and Treatments
- Neurological disorders and treatments
- Brain Tumor Detection and Classification
Papers in
-
- Artificial Intelligence in Healthcare 7
-
- Imbalanced Data Classification Techniques 2
- AI in cancer detection 2
- Machine Learning in Healthcare 2
- Co-authors
- Anurag Jain (11 shared papers)Tarun Gulati (7 shared papers)Hadeel Alharbi (1 shared paper)Pooja Rani (10 shared papers)Ravi Kumar Sachdeva (8 shared papers)Kawther A. Al‐Dhlan (1 shared paper)Rajneesh Kumar (3 shared papers)Celestine Iwendi (1 shared paper)
- Journals
- Arabian Journal for Science and Engineering (2 papers)Journal of Reliable Intelligent Environments (1 paper)Archives of Computational Methods in Engineering (1 paper)International Journal of Speech Technology (1 paper)Neural Computing and Applications (1 paper)
- Partner nations
- IndiaSaudi ArabiaUnited Kingdom
In The Last Decade
Rohit Lamba
15 papers receiving 255 citations
Peers
Comparison fields: 5 of 58
- Health Information Management 62
- Neurology 68
- Physiology 108
- Signal Processing 36
- Neurology 25
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 19 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 | 84 | |
| 2 | 2021 | 36 | |
| 3 | 2022 | 35 | |
| 4 | 2024 | 22 | |
| 5 | 2024 | 16 | |
| 6 | 2022 | 15 | |
| 7 | 2020 | 12 | |
| 8 | 2022 | 11 | |
| 9 | 2020 | 11 | |
| 10 | 2023 | 7 | |
| 11 | 2023 | 6 | |
| 12 | RECOGNIZING VOICE FOR NUMERICS USING MFCC AND DTW | 2013 | 3 |
| 13 | 2025 | 2 | |
| 14 | 2024 | 2 | |
| 15 | 2022 | 1 | |
| 16 | 2023 | 0 | |
| 17 | 2023 | 0 |
About Rohit Lamba
Rohit Lamba is a scholar working on Health Information Management, Artificial Intelligence, Physiology, Neurology and Neurology, having authored 17 papers that have together received 263 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), AI in cancer detection (2 papers), Machine Learning in Healthcare (2 papers) and Machine Learning in Bioinformatics (1 paper). The work is most often cited by research in Health Information Management (62 citations), Neurology (68 citations), Physiology (108 citations), Signal Processing (36 citations) and Neurology (25 citations). Rohit Lamba has collaborated with scholars based in India, Saudi Arabia and United Kingdom. Frequent co-authors include Anurag Jain, Tarun Gulati, Hadeel Alharbi, Pooja Rani, Ravi Kumar Sachdeva, Kawther A. Al‐Dhlan, Rajneesh Kumar, Celestine Iwendi, Manoj Kumar and Arwa N. Aledaily. Their work appears in journals such as Arabian Journal for Science and Engineering, Journal of Reliable Intelligent Environments, Archives of Computational Methods in Engineering, International Journal of Speech Technology and Neural Computing 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.