Laboni Akter
Impact in
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- Artificial Intelligence in Healthcare
Papers in
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- Artificial Intelligence in Healthcare 6
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- Imbalanced Data Classification Techniques 3
- AI in cancer detection 2
- Co-authors
- M. Raihan (7 shared papers)Md. Milon Islam (2 shared papers)Etu Podder (1 shared paper)Md. Rezwanul Haque (1 shared paper)Mabrook Al‐Rakhami (1 shared paper)Md. Mehedi Hassan (4 shared papers)Khan Md. Hasib (1 shared paper)Md. Mahedi Hassan (1 shared paper)
- Journals
- The Journal of Engineering (1 paper)Data Intelligence (1 paper)PLoS ONE (1 paper)Intelligent Automation & Soft Computing (1 paper)SN Computer Science (1 paper)
- Partner nations
- BangladeshAustraliaIndia
In The Last Decade
Laboni Akter
14 papers receiving 298 citations
Peers
Comparison fields: 5 of 85
- Health Information Management 83
- Health Informatics 6
- Artificial Intelligence 138
- Water Science and Technology 57
- Neurology 34
Countries citing papers authored by Laboni Akter
This map shows the geographic impact of Laboni Akter'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 Laboni Akter with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Laboni Akter more than expected).
Fields of papers citing papers by Laboni Akter
This network shows the impact of papers produced by Laboni Akter. 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 Laboni Akter. The network helps show where Laboni Akter may publish in the future.
Co-authors
The 25 scholars most cited alongside Laboni Akter, 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 | 2020 | 84 | |
| 2 | 2021 | 71 | |
| 3 | 2021 | 53 | |
| 4 | 2021 | 27 | |
| 5 | 2023 | 27 | |
| 6 | 2020 | 16 | |
| 7 | 2021 | 15 | |
| 8 | 2021 | 9 | |
| 9 | 2014 | 6 | |
| 10 | 2021 | 3 | |
| 11 | 2025 | 2 | |
| 12 | 2021 | 2 | |
| 13 | 2020 | 2 | |
| 14 | 2024 | 1 | |
| 15 | 2023 | 0 |
About Laboni Akter
Laboni Akter is a scholar working on Health Information Management, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Neurology and Immunology, having authored 15 papers that have together received 318 indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare (6 papers), Imbalanced Data Classification Techniques (3 papers), Brain Tumor Detection and Classification (2 papers), AI in cancer detection (2 papers), Hepatocellular Carcinoma Treatment and Prognosis (1 paper), COVID-19 diagnosis using AI (1 paper), Galectins and Cancer Biology (1 paper) and Water Quality Monitoring Technologies (1 paper). The work is most often cited by research in Health Information Management (83 citations), Health Informatics (6 citations), Artificial Intelligence (138 citations), Water Science and Technology (57 citations) and Neurology (34 citations). Laboni Akter has collaborated with scholars based in Bangladesh, Australia and India. Frequent co-authors include M. Raihan, Md. Milon Islam, Etu Podder, Md. Rezwanul Haque, Mabrook Al‐Rakhami, Md. Mehedi Hassan, Khan Md. Hasib, Md. Mahedi Hassan, Sadika Zaman and Tanvir Ahammed. Their work appears in journals such as The Journal of Engineering, Data Intelligence, PLoS ONE, Intelligent Automation & Soft Computing and SN Computer Science.
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.