Rajib Kumar Halder
Impact in
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- Artificial Intelligence in Healthcare
Papers in
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- Imbalanced Data Classification Techniques 2
- Machine Learning in Healthcare 2
- Machine Learning and Data Classification 2
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- Machine Learning in Bioinformatics 3
- Epigenetics and DNA Methylation 2
- Co-authors
- Mohammed Nasir Uddin (10 shared papers)Md. Ashraf Uddin (5 shared papers)Sunil Aryal (3 shared papers)Ansam Khraisat (2 shared papers)Sajeeb Saha (2 shared papers)Sabbir Ahmed (1 shared paper)Mohammad Abu Tareq Rony (1 shared paper)Ammar Alazab (1 shared paper)
- Journals
- Journal Of Big Data (1 paper)Journal of Pathology Informatics (1 paper)Genes (1 paper)Intelligence-Based Medicine (1 paper)Informatics in Medicine Unlocked (2 papers)
- Partner nations
- BangladeshAustralia
In The Last Decade
Rajib Kumar Halder
8 papers receiving 243 citations
Rajib Kumar Halder's Hit Papers
Peers
Comparison fields: 5 of 86
- Health Information Management 54
- Health Informatics 4
- Medical Laboratory Technology 4
- Artificial Intelligence 80
- Information Systems 27
Countries citing papers authored by Rajib Kumar Halder
This map shows the geographic impact of Rajib Kumar Halder'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 Rajib Kumar Halder with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rajib Kumar Halder more than expected).
Fields of papers citing papers by Rajib Kumar Halder
This network shows the impact of papers produced by Rajib Kumar Halder. 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 Rajib Kumar Halder. The network helps show where Rajib Kumar Halder may publish in the future.
Co-authors
The 11 scholars most cited alongside Rajib Kumar Halder, 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 | Enhancing K-nearest neighbor algorithm: a comprehensive review and performance analysis of modifications Hit paper breakdown → | 2024 | 157 |
| 2 | 2021 | 36 | |
| 3 | 2024 | 29 | |
| 4 | 2021 | 19 | |
| 5 | 2023 | 5 | |
| 6 | 2023 | 3 | |
| 7 | 2025 | 1 | |
| 8 | 2025 | 1 | |
| 9 | 2025 | 0 | |
| 10 | 2025 | 0 | |
| 11 | 2023 | 0 |
About Rajib Kumar Halder
Rajib Kumar Halder is a scholar working on Artificial Intelligence, Molecular Biology, Health Information Management, Computer Vision and Pattern Recognition and Computer Networks and Communications, having authored 11 papers that have together received 251 indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare (3 papers), Machine Learning in Bioinformatics (3 papers), Imbalanced Data Classification Techniques (2 papers), Epigenetics and DNA Methylation (2 papers), Machine Learning in Healthcare (2 papers), Face and Expression Recognition (2 papers), Machine Learning and Data Classification (2 papers) and Advanced Image and Video Retrieval Techniques (2 papers). The work is most often cited by research in Health Information Management (54 citations), Health Informatics (4 citations), Medical Laboratory Technology (4 citations), Artificial Intelligence (80 citations) and Information Systems (27 citations). Rajib Kumar Halder has collaborated with scholars based in Bangladesh and Australia. Frequent co-authors include Mohammed Nasir Uddin, Md. Ashraf Uddin, Sunil Aryal, Ansam Khraisat, Sajeeb Saha, Sabbir Ahmed, Mohammad Abu Tareq Rony, Ammar Alazab, Md. Aminul Islam and Fatema Akter. Their work appears in journals such as Journal Of Big Data, Journal of Pathology Informatics, Genes, Intelligence-Based Medicine and Informatics in Medicine Unlocked.
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.