Moloud Abdar

8.8k total citations · 4 hit papers
85 papers, 6.0k citations indexed

About

Moloud Abdar is a scholar working on Artificial Intelligence, Health Information Management and Information Systems. According to data from OpenAlex, Moloud Abdar has authored 85 papers receiving a total of 6.0k indexed citations (citations by other indexed papers that have themselves been cited), including 50 papers in Artificial Intelligence, 19 papers in Health Information Management and 13 papers in Information Systems. Recurrent topics in Moloud Abdar's work include Artificial Intelligence in Healthcare (19 papers), Imbalanced Data Classification Techniques (19 papers) and Data Mining Algorithms and Applications (9 papers). Moloud Abdar is often cited by papers focused on Artificial Intelligence in Healthcare (19 papers), Imbalanced Data Classification Techniques (19 papers) and Data Mining Algorithms and Applications (9 papers). Moloud Abdar collaborates with scholars based in Australia, Iran and Canada. Moloud Abdar's 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 and has published in prestigious journals such as SHILAP Revista de lepidopterología, Renewable and Sustainable Energy Reviews and PLoS ONE.

In The Last Decade

Moloud Abdar

82 papers receiving 5.7k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

A review of uncertainty quantification in deep learning: Techniques, applications and challenges

2021 1.5k citations Moloud Abdar, Farhad Pourpanah et al. Information Fusion profile →
ABCDM: An Attention-based Bidirectional CNN-RNN Deep Model for sentiment analysis

2020 519 citations Mohammad Ehsan Basiri, Shahla Nemati et al. profile →
A new machine learning technique for an accurate diagnosis of coronary artery disease

2019 248 citations Moloud Abdar, U. Rajendra Acharya et al. profile →
A Review of Generalized Zero-Shot Learning Methods

2022 239 citations Farhad Pourpanah, Moloud Abdar et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Moloud Abdar Australia	36	3.0k	910	804	740	405	85	6.0k
Shaker El–Sappagh Egypt	39	2.3k 0.8×	1.0k 1.1×	815 1.0×	443 0.6×	210 0.5×	146	5.3k
Igor Kononenko Slovenia	26	3.7k 1.2×	644 0.7×	489 0.6×	1.1k 1.5×	258 0.6×	117	7.9k
Cynthia Rudin United States	38	5.2k 1.7×	276 0.3×	571 0.7×	728 1.0×	221 0.5×	172	10.1k
Simon Fong Macao	39	2.8k 0.9×	321 0.4×	755 0.9×	942 1.3×	176 0.4×	428	7.1k
Iqbal H. Sarker Bangladesh	32	2.6k 0.9×	429 0.5×	599 0.7×	723 1.0×	160 0.4×	102	8.4k
Jianping Li China	35	1.9k 0.6×	939 1.0×	690 0.9×	1.2k 1.6×	173 0.4×	366	5.2k
Jonathan M. Garibaldi United Kingdom	39	2.4k 0.8×	562 0.6×	324 0.4×	808 1.1×	291 0.7×	274	6.5k
Laith Alzubaidi Australia	27	2.2k 0.7×	244 0.3×	1.2k 1.5×	1.4k 1.9×	128 0.3×	83	7.4k
Ahmad Taher Azar Egypt	45	2.4k 0.8×	416 0.5×	752 0.9×	1.7k 2.3×	143 0.4×	373	8.1k
Andrew P. Bradley Australia	33	4.0k 1.3×	475 0.5×	1.6k 2.1×	2.0k 2.7×	227 0.6×	153	9.8k

Countries citing papers authored by Moloud Abdar

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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 of co-authors of Moloud Abdar

This figure shows the co-authorship network connecting the top 25 collaborators of Moloud Abdar. A scholar is included among the top collaborators of Moloud Abdar based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Moloud Abdar. Moloud Abdar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Abdar, Moloud, Abbas Khosravi, Uwe Aickelin, et al.. (2025). Survey on Leveraging Uncertainty Estimation Towards Trustworthy Deep Neural Networks: The Case of Reject Option and Post-training Processing. ACM Computing Surveys. 57(9). 1–35.

Abdar, Moloud, et al.. (2024). Attention-guided hierarchical fusion U-Net for uncertainty-driven medical image segmentation. Information Fusion. 115. 102719–102719. 18 indexed citations

Salari, Vahid, et al.. (2023). Quantum face recognition protocol with ghost imaging. Scientific Reports. 13(1). 2401–2401. 8 indexed citations

Abdar, Moloud, Farzad Masoudkabir, Leonardo Rundo, et al.. (2023). Binarized multi-gate mixture of Bayesian experts for cardiac syndrome X diagnosis: A clinician-in-the-loop scenario with a belief-uncertainty fusion paradigm. Information Fusion. 97. 101813–101813. 9 indexed citations

Abdar, Moloud, Fatemeh Safara, Seyedali Mirjalili, et al.. (2023). Improved binary differential evolution with dimensionality reduction mechanism and binary stochastic search for feature selection. Applied Soft Computing. 151. 111141–111141. 12 indexed citations

Qazani, Mohammad Reza Chalak, Houshyar Asadi, Yutao Chen, et al.. (2023). An Optimal Nonlinear Model Predictive Control- Based Motion Cueing Algorithm Using Cascade Optimization and Human Interaction. IEEE Transactions on Intelligent Transportation Systems. 24(9). 9191–9202. 8 indexed citations

Gilbert, Alexandra, J. Lilley, Moloud Abdar, et al.. (2023). Toxicity Prediction in Pelvic Radiotherapy Using Multiple Instance Learning and Cascaded Attention Layers. IEEE Journal of Biomedical and Health Informatics. 27(4). 1958–1966. 2 indexed citations

Abdar, Moloud, Soorena Salari, Hak‐Keung Lam, et al.. (2022). UncertaintyFuseNet: Robust uncertainty-aware hierarchical feature fusion model with Ensemble Monte Carlo Dropout for COVID-19 detection. Information Fusion. 90. 364–381. 76 indexed citations

Abdar, Moloud, Leonardo Rundo, Petia Radeva, et al.. (2022). Hercules: Deep Hierarchical Attentive Multilevel Fusion Model With Uncertainty Quantification for Medical Image Classification. IEEE Transactions on Industrial Informatics. 19(1). 274–285. 47 indexed citations

10.

Abdar, Moloud, Farhad Pourpanah, Sadiq Hussain, et al.. (2021). A review of uncertainty quantification in deep learning: Techniques, applications and challenges. Information Fusion. 76. 243–297. 1491 indexed citations breakdown →

11.

Zomorodi‐Moghadam, Mariam, Moloud Abdar, Hamid Noori, et al.. (2021). A novel approach based on genetic algorithm to speed up the discovery of classification rules on GPUs. Knowledge-Based Systems. 231. 107419–107419. 7 indexed citations

12.

Afzal, Muhammad Tanvir, et al.. (2020). A comprehensive analysis of adverb types for mining user sentiments on amazon product reviews. World Wide Web. 23(3). 1811–1829. 35 indexed citations

13.

Basiri, Mohammad Ehsan, et al.. (2019). Improving Sentiment Polarity Detection Through Target Identification. IEEE Transactions on Computational Social Systems. 7(1). 113–128. 19 indexed citations

14.

Nemati, Shahla, et al.. (2019). A Hybrid Latent Space Data Fusion Method for Multimodal Emotion Recognition. IEEE Access. 7. 172948–172964. 65 indexed citations

15.

Basiri, Mohammad Ehsan, et al.. (2019). The effect of aggregation methods on sentiment classification in Persian reviews. Enterprise Information Systems. 14(9-10). 1394–1421. 20 indexed citations

16.

Abdar, Moloud, U. Rajendra Acharya, Nizal Sarrafzadegan, & Vladimir Makarenkov. (2019). NE-nu-SVC: A New Nested Ensemble Clinical Decision Support System for Effective Diagnosis of Coronary Artery Disease. IEEE Access. 7. 167605–167620. 73 indexed citations

17.

Abdar, Moloud & Mariam Zomorodi‐Moghadam. (2018). Impact of Patients’ Gender on Parkinson’s disease using Classification Algorithms. SHILAP Revista de lepidopterología. 18 indexed citations

18.

Shahmoradi, Leila, et al.. (2018). Predicting risk of acute appendicitis: A comparison of artificial neural network and logistic regression models. SHILAP Revista de lepidopterología. 7 indexed citations

19.

Abdar, Moloud, et al.. (2017). Crowd Preference Mining and Analysis Based on Regional Characteristics on Airbnb. 1–6. 5 indexed citations

20.

Abdar, Moloud. (2015). Using Decision Trees in Data Mining for Predicting Factors Influencing of Heart Disease. 30 indexed citations

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.

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