Moloud Abdar
- Health Information Management top 0.05%
- Artificial Intelligence in Healthcare 19
- Health Informatics top 1%
- Artificial Intelligence top 0.2%
- Imbalanced Data Classification Techniques 19
- AI in cancer detection 7
- Machine Learning and Data Classification 7
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- Data Mining Algorithms and Applications 9
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- Transportation and Mobility Innovations 7
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- ECG Monitoring and Analysis 7
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- Sharing Economy and Platforms 7
Moloud Abdar
82 papers receiving 5.7k citations
Hit Papers
Peers
Comparison fields: 5 of 196
- Health Information Management 910
- Health Informatics 146
- Artificial Intelligence 3.0k
- Medical Laboratory Technology 60
- Computer Vision and Pattern Recognition 740
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-authorship network
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
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 18 | |
| 2 | 2024 | 6 | |
| 3 | 2023 | 8 | |
| 4 | 2023 | 9 | |
| 5 | 2023 | 2 | |
| 6 | 2023 | 12 | |
| 7 | 2023 | 8 | |
| 8 | 2022 | 47 | |
| 9 | 2022 | 76 | |
| 10 | A review of uncertainty quantification in deep learning: Techniques, applications and challengesbreakdown → | 2021 | 1491 |
| 11 | 2021 | 7 | |
| 12 | 2020 | 35 | |
| 13 | 2019 | 65 | |
| 14 | 2019 | 19 | |
| 15 | 2019 | 20 | |
| 16 | 2019 | 177 | |
| 17 | 2019 | 51 | |
| 18 | 2018 | 18 | |
| 19 | Predicting risk of acute appendicitis: A comparison of artificial neural network and logistic regression models | 2018 | 7 |
| 20 | Using Decision Trees in Data Mining for Predicting Factors Influencing of Heart Disease | 2015 | 30 |
About Moloud Abdar
Moloud Abdar is a scholar working on Health Information Management, Artificial Intelligence and Health Informatics, having authored 85 papers that have together received 6.0k indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare (19 papers), Imbalanced Data Classification Techniques (19 papers), Data Mining Algorithms and Applications (9 papers), Transportation and Mobility Innovations (7 papers), ECG Monitoring and Analysis (7 papers), AI in cancer detection (7 papers), Machine Learning and Data Classification (7 papers) and Sharing Economy and Platforms (7 papers). The work is most often cited by research in Health Information Management (910 citations), Health Informatics (146 citations) and Artificial Intelligence (3.0k citations). Moloud Abdar has collaborated with scholars based in Australia, Iran and Canada. 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 Knowledge-Based Systems, IEEE Access, Information Fusion, Information Sciences and Applied Soft Computing.
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.