Pradip Dhal
Impact in
- Artificial Intelligence top 5%
- Metaheuristic Optimization Algorithms Research
- Machine Learning and Data Classification
- Text and Document Classification Technologies
- Evolutionary Algorithms and Applications
- Anomaly Detection Techniques and Applications
- Health Information Management top 10%
- Artificial Intelligence in Healthcare
Papers in
-
- Text and Document Classification Technologies 6
- Metaheuristic Optimization Algorithms Research 4
- Machine Learning and Data Classification 2
- AI in cancer detection 2
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- Spam and Phishing Detection 3
- Web Data Mining and Analysis 2
- Co-authors
- Chandrashekhar Azad (10 shared papers)Buddhadeb Pradhan (2 shared papers)Debahuti Mishra (1 shared paper)Ugo Fiore (1 shared paper)Diptendu Sinha Roy (1 shared paper)
- Journals
- Applied Soft Computing (2 papers)Applied Intelligence (1 paper)Multimedia Tools and Applications (1 paper)Neural Computing and Applications (1 paper)Information Fusion (1 paper)
- Partner nations
- IndiaItalySaudi Arabia
In The Last Decade
Pradip Dhal
13 papers receiving 421 citations
Pradip Dhal's Hit Papers
Peers
Comparison fields: 5 of 101
- Artificial Intelligence 204
- Health Information Management 23
- Computer Vision and Pattern Recognition 78
- Signal Processing 27
- Health Informatics 3
Countries citing papers authored by Pradip Dhal
This map shows the geographic impact of Pradip Dhal'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 Pradip Dhal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pradip Dhal more than expected).
Fields of papers citing papers by Pradip Dhal
This network shows the impact of papers produced by Pradip Dhal. 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 Pradip Dhal. The network helps show where Pradip Dhal may publish in the future.
Co-authors
The 5 scholars most cited alongside Pradip Dhal, 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 | A comprehensive survey on feature selection in the various fields of machine learning Hit paper breakdown → | 2021 | 292 |
| 2 | 2021 | 54 | |
| 3 | 2022 | 15 | |
| 4 | 2023 | 14 | |
| 5 | 2023 | 9 | |
| 6 | 2024 | 8 | |
| 7 | 2022 | 7 | |
| 8 | 2020 | 7 | |
| 9 | 2022 | 7 | |
| 10 | 2025 | 5 | |
| 11 | 2022 | 5 | |
| 12 | 2025 | 4 | |
| 13 | 2023 | 1 | |
| 14 | 2025 | 0 |
About Pradip Dhal
Pradip Dhal is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Biomedical Engineering, having authored 14 papers that have together received 428 indexed citations. Recurring topics across this work include Text and Document Classification Technologies (6 papers), Metaheuristic Optimization Algorithms Research (4 papers), Spam and Phishing Detection (3 papers), Web Data Mining and Analysis (2 papers), Machine Learning and Data Classification (2 papers), AI in cancer detection (2 papers), Artificial Intelligence in Healthcare (1 paper) and Poxvirus research and outbreaks (1 paper). The work is most often cited by research in Artificial Intelligence (204 citations), Health Information Management (23 citations), Computer Vision and Pattern Recognition (78 citations), Signal Processing (27 citations) and Health Informatics (3 citations). Pradip Dhal has collaborated with scholars based in India, Italy and Saudi Arabia. Frequent co-authors include Chandrashekhar Azad, Buddhadeb Pradhan, Debahuti Mishra, Ugo Fiore and Diptendu Sinha Roy. Their work appears in journals such as Applied Soft Computing, Applied Intelligence, Multimedia Tools and Applications, Neural Computing and Applications and Information Fusion.
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.