Dalal Bardou
Impact in
- Artificial Intelligence top 5%
- AI in cancer detection
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- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
Papers in
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- Advanced Graph Neural Networks 7
- AI in cancer detection 3
- Domain Adaptation and Few-Shot Learning 3
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- Complex Network Analysis Techniques 13
- Opinion Dynamics and Social Influence 9
- Co-authors
- Kun Zhang (1 shared paper)Kun Zhang (3 shared papers)Ting Zhang (11 shared papers)Gaohang Yu (8 shared papers)Zhuo Li (1 shared paper)Xiabi Liu (1 shared paper)Ying Cai (3 shared papers)Xiaohong Ma (1 shared paper)
In The Last Decade
Dalal Bardou
22 papers receiving 677 citations
Dalal Bardou's Hit Papers
Peers
Comparison fields: 5 of 96
- Artificial Intelligence 384
- Radiology, Nuclear Medicine and Imaging 271
- Computer Vision and Pattern Recognition 200
- Signal Processing 100
- Computational Mathematics 5
Countries citing papers authored by Dalal Bardou
This map shows the geographic impact of Dalal Bardou'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 Dalal Bardou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dalal Bardou more than expected).
Fields of papers citing papers by Dalal Bardou
This network shows the impact of papers produced by Dalal Bardou. 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 Dalal Bardou. The network helps show where Dalal Bardou may publish in the future.
Co-authors
The 19 scholars most cited alongside Dalal Bardou, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Classification of Breast Cancer Based on Histology Images Using Convolutional Neural Networks Hit paper breakdown → | 2018 | 296 |
| 2 | 2018 | 170 | |
| 3 | 2021 | 62 | |
| 4 | 2019 | 30 | |
| 5 | 2023 | 24 | |
| 6 | 2022 | 19 | |
| 7 | 2023 | 18 | |
| 8 | 2023 | 15 | |
| 9 | 2022 | 14 | |
| 10 | 2019 | 11 | |
| 11 | 2022 | 8 | |
| 12 | 2023 | 7 | |
| 13 | 2025 | 6 | |
| 14 | 2019 | 5 | |
| 15 | 2022 | 5 | |
| 16 | 2020 | 4 | |
| 17 | 2025 | 3 | |
| 18 | 2024 | 2 | |
| 19 | 2019 | 2 | |
| 20 | 2024 | 1 |
About Dalal Bardou
Dalal Bardou is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics, Computer Vision and Pattern Recognition, Computer Networks and Communications and Radiology, Nuclear Medicine and Imaging, having authored 26 papers that have together received 704 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (13 papers), Opinion Dynamics and Social Influence (9 papers), Advanced Graph Neural Networks (7 papers), AI in cancer detection (3 papers), Domain Adaptation and Few-Shot Learning (3 papers), Multimodal Machine Learning Applications (2 papers), Network Traffic and Congestion Control (2 papers) and Radiomics and Machine Learning in Medical Imaging (2 papers). The work is most often cited by research in Artificial Intelligence (384 citations), Radiology, Nuclear Medicine and Imaging (271 citations), Computer Vision and Pattern Recognition (200 citations), Signal Processing (100 citations) and Computational Mathematics (5 citations). Dalal Bardou has collaborated with scholars based in China, Algeria and France. Frequent co-authors include Kun Zhang, Kun Zhang, Ting Zhang, Gaohang Yu, Zhuo Li, Xiabi Liu, Ying Cai, Xiaohong Ma, Shanzhou Niu and Yanqiu Liu. Their work appears in journals such as Journal of the Physical Society of Japan, IEEE Access, Expert Systems with Applications, Physics Letters A and Chaos Solitons & Fractals.
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.