Moloud Abdar
Impact in
- Health Information Management top 0.05%
- Artificial Intelligence in Healthcare
- Health Informatics top 0.5%
Papers in
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- Imbalanced Data Classification Techniques 18
- AI in cancer detection 7
- Machine Learning and Data Classification 7
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- Artificial Intelligence in Healthcare 20
- Co-authors
- U. Rajendra Acharya (29 shared papers)Vladimir Makarenkov (16 shared papers)Abbas Khosravi (28 shared papers)Saeid Nahavandi (23 shared papers)Mohammad Ehsan Basiri (12 shared papers)Paweł Pławiak (16 shared papers)Shahla Nemati (6 shared papers)Farhad Pourpanah (5 shared papers)
In The Last Decade
Moloud Abdar
85 papers receiving 6.4k citations
Moloud Abdar's Hit Papers
Peers
Comparison fields: 5 of 195
- Health Information Management 984
- Health Informatics 151
- Artificial Intelligence 3.2k
- Medical Laboratory Technology 61
- Radiology, Nuclear Medicine and Imaging 771
Countries citing papers authored by Moloud Abdar
This map shows the geographic impact of Moloud Abdar'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 Moloud Abdar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Moloud Abdar more than expected).
Fields of papers citing papers by Moloud Abdar
This network shows the impact of papers produced by Moloud Abdar. 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 Moloud Abdar. The network helps show where Moloud Abdar may publish in the future.
Co-authors
The 25 scholars most cited alongside Moloud Abdar, 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 88 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | A review of uncertainty quantification in deep learning: Techniques, applications and challenges Hit paper breakdown → | 2021 | 1686 |
| 2 | ABCDM: An Attention-based Bidirectional CNN-RNN Deep Model for sentiment analysis Hit paper breakdown → | 2020 | 571 |
| 3 | A Review of Generalized Zero-Shot Learning Methods Hit paper breakdown → | 2022 | 271 |
| 4 | A new machine learning technique for an accurate diagnosis of coronary artery disease Hit paper breakdown → | 2019 | 263 |
| 5 | 2020 | 203 | |
| 6 | Uncertainty quantification in skin cancer classification using three-way decision-based Bayesian deep learning Hit paper breakdown → | 2021 | 192 |
| 7 | 2019 | 188 | |
| 8 | 2018 | 188 | |
| 9 | 2021 | 144 | |
| 10 | 2019 | 141 | |
| 11 | 2016 | 125 | |
| 12 | 2019 | 120 | |
| 13 | 2020 | 112 | |
| 14 | 2022 | 105 | |
| 15 | 2019 | 102 | |
| 16 | 2017 | 99 | |
| 17 | 2018 | 94 | |
| 18 | 2020 | 84 | |
| 19 | 2015 | 83 | |
| 20 | 2020 | 83 |
About Moloud Abdar
Moloud Abdar is a scholar working on Artificial Intelligence, Health Information Management, Information Systems, Computer Vision and Pattern Recognition and Cardiology and Cardiovascular Medicine, having authored 88 papers that have together received 6.6k indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare (20 papers), Imbalanced Data Classification Techniques (18 papers), Data Mining Algorithms and Applications (9 papers), ECG Monitoring and Analysis (8 papers), Transportation and Mobility Innovations (7 papers), Sharing Economy and Platforms (7 papers), AI in cancer detection (7 papers) and Machine Learning and Data Classification (7 papers). The work is most often cited by research in Health Information Management (984 citations), Health Informatics (151 citations), Artificial Intelligence (3.2k citations), Medical Laboratory Technology (61 citations) and Radiology, Nuclear Medicine and Imaging (771 citations). Moloud Abdar has collaborated with scholars based in Australia, Canada and Iran. Frequent co-authors include U. Rajendra Acharya, Vladimir Makarenkov, Abbas Khosravi, Saeid Nahavandi, Mohammad Ehsan Basiri, Paweł Pławiak, Shahla Nemati, Farhad Pourpanah, Sadiq Hussain and Li Liu. Their work appears in journals such as Information Fusion, IEEE Access, Knowledge-Based Systems, Computers in Biology and Medicine and Information Sciences.
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.