Muhammad E. H. Chowdhury

12.7k total citations · 6 hit papers
285 papers, 7.6k citations indexed

About

Muhammad E. H. Chowdhury is a scholar working on Biomedical Engineering, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence. According to data from OpenAlex, Muhammad E. H. Chowdhury has authored 285 papers receiving a total of 7.6k indexed citations (citations by other indexed papers that have themselves been cited), including 82 papers in Biomedical Engineering, 64 papers in Radiology, Nuclear Medicine and Imaging and 40 papers in Artificial Intelligence. Recurrent topics in Muhammad E. H. Chowdhury's work include COVID-19 diagnosis using AI (36 papers), Non-Invasive Vital Sign Monitoring (32 papers) and EEG and Brain-Computer Interfaces (27 papers). Muhammad E. H. Chowdhury is often cited by papers focused on COVID-19 diagnosis using AI (36 papers), Non-Invasive Vital Sign Monitoring (32 papers) and EEG and Brain-Computer Interfaces (27 papers). Muhammad E. H. Chowdhury collaborates with scholars based in Qatar, Bangladesh and Malaysia. Muhammad E. H. Chowdhury's co-authors include Amith Khandakar, Mohammad Tariqul Islam, Tawsifur Rahman, Mamun Bin Ibne Reaz, Muhammad Salman Khan, Zaid Bin Mahbub, Khandaker Reajul Islam, Muhammad Abdul Kadir, Serkan Kıranyaz and Anas Tahir and has published in prestigious journals such as SHILAP Revista de lepidopterología, NeuroImage and Scientific Reports.

In The Last Decade

Muhammad E. H. Chowdhury

253 papers receiving 7.3k citations

Hit Papers

Can AI Help in Screening ... 2020 2026 2022 2024 2020 2021 2020 2020 2021 250 500 750 1000
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.

  1. Can AI Help in Screening Viral and COVID-19 Pneumonia?
    2020 1.2k citations Muhammad E. H. Chowdhury, Tawsifur Rahman et al. IEEE Access profile →
  2. Exploring the effect of image enhancement techniques on COVID-19 detection using chest X-ray images
    2021 672 citations Tawsifur Rahman, Amith Khandakar et al. Computers in Biology and Medicine profile →
  3. Transfer Learning with Deep Convolutional Neural Network (CNN) for Pneumonia Detection Using Chest X-ray
    2020 394 citations Tawsifur Rahman, Muhammad E. H. Chowdhury et al. profile →
  4. Reliable Tuberculosis Detection Using Chest X-Ray With Deep Learning, Segmentation and Visualization
    2020 375 citations Tawsifur Rahman, Amith Khandakar et al. IEEE Access profile →
  5. Automatic and Reliable Leaf Disease Detection Using Deep Learning Techniques
    2021 213 citations Muhammad E. H. Chowdhury, Tawsifur Rahman et al. profile →
  6. COVID-19 infection localization and severity grading from chest X-ray images
    2022 116 citations Anas Tahir, Muhammad E. H. Chowdhury et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Muhammad E. H. Chowdhury Qatar 39 3.3k 2.3k 1.4k 949 706 285 7.6k
Amith Khandakar Qatar 34 3.0k 0.9× 2.1k 0.9× 1.0k 0.7× 801 0.8× 642 0.9× 163 6.2k
Yuanyuan Wang China 42 3.3k 1.0× 1.2k 0.6× 1.9k 1.3× 1.1k 1.1× 914 1.3× 533 8.2k
Abdulkadir Şengür Türkiye 52 1.6k 0.5× 2.6k 1.2× 740 0.5× 1.6k 1.7× 503 0.7× 229 8.7k
Dimitrios I. Fotiadis Greece 47 1.8k 0.5× 1.6k 0.7× 1.8k 1.3× 647 0.7× 902 1.3× 404 10.2k
E. Y. K. Ng Singapore 55 5.5k 1.7× 747 0.3× 2.3k 1.7× 1.2k 1.3× 663 0.9× 439 11.4k
Mamun Bin Ibne Reaz Malaysia 36 1.3k 0.4× 1.7k 0.7× 2.9k 2.1× 776 0.8× 328 0.5× 355 8.2k
Özal Yıldırım Türkiye 29 2.4k 0.7× 2.1k 0.9× 1.0k 0.8× 954 1.0× 799 1.1× 77 6.7k
Heye Zhang China 40 1.8k 0.5× 609 0.3× 1.5k 1.1× 1.1k 1.1× 505 0.7× 154 4.8k
Somaya Al-Máadeed Qatar 46 1.2k 0.4× 1.7k 0.7× 1.3k 0.9× 2.7k 2.8× 230 0.3× 292 7.0k
Kemal Polat Türkiye 46 805 0.2× 2.9k 1.3× 1.0k 0.7× 1.3k 1.4× 261 0.4× 239 7.9k

Countries citing papers authored by Muhammad E. H. Chowdhury

Since Specialization
Citations

This map shows the geographic impact of Muhammad E. H. Chowdhury'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 Muhammad E. H. Chowdhury with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Muhammad E. H. Chowdhury more than expected).

Fields of papers citing papers by Muhammad E. H. Chowdhury

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Muhammad E. H. Chowdhury. 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 Muhammad E. H. Chowdhury. The network helps show where Muhammad E. H. Chowdhury may publish in the future.

Co-authorship network of co-authors of Muhammad E. H. Chowdhury

This figure shows the co-authorship network connecting the top 25 collaborators of Muhammad E. H. Chowdhury. A scholar is included among the top collaborators of Muhammad E. H. Chowdhury 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 Muhammad E. H. Chowdhury. Muhammad E. H. Chowdhury is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Faisal, Md. Ahasan Atick, et al.. (2025). Machine learning for predicting outcomes of transcatheter aortic valve implantation: A systematic review. International Journal of Medical Informatics. 197. 105840–105840. 2 indexed citations
3.
Chowdhury, Muhammad E. H., et al.. (2025). Artificial Intelligence and Machine Learning in Lung Cancer: Advances in Imaging, Detection, and Prognosis. Cancers. 17(24). 3985–3985.
4.
Rahman, Rakibur, Qing Luo, Ke Wang, et al.. (2025). Classification of glioma grade and Ki-67 level prediction in MRI data: A SHAP-driven interpretation. Computerized Medical Imaging and Graphics. 124. 102578–102578.
5.
Chowdhury, Muhammad E. H., et al.. (2024). A novel dataset of Gupta archer type coins for machine learning-based classification. Data in Brief. 57. 110934–110934. 1 indexed citations
6.
Chowdhury, Moajjem Hossain, Moajjem Hossain Chowdhury, Mamun Bin Ibne Reaz, et al.. (2024). ROSE-Net: Leveraging remote photoplethysmography to estimate oxygen saturation using deep learning. Biomedical Signal Processing and Control. 100. 107105–107105. 4 indexed citations
7.
Rahman, Tawsifur, Amith Khandakar, Susu M. Zughaier, et al.. (2024). TB-CXRNet: Tuberculosis and Drug-Resistant Tuberculosis Detection Technique Using Chest X-ray Images. Cognitive Computation. 16(3). 1393–1412. 11 indexed citations
8.
Chowdhury, Muhammad E. H., Amith Khandakar, Nasser Al‐Emadi, et al.. (2024). GearFaultNet: Novel Network for Automatic and Early Detection of Gearbox Faults. IEEE Access. 12. 188755–188765. 1 indexed citations
9.
Chowdhury, Moajjem Hossain, Moajjem Hossain Chowdhury, Muhammad E. H. Chowdhury, Muhammad E. H. Chowdhury, & Abdulrahman Alqahtani. (2024). MMG-net: Multi modal approach to estimate blood glucose using multi-stream and cross modality attention. Biomedical Signal Processing and Control. 92. 105975–105975. 12 indexed citations
10.
Mahmud, Sakib, Muhammad E. H. Chowdhury, Muhammad E. H. Chowdhury, et al.. (2024). Restoration of magnetohydrodynamic-corrupted 12-lead electrocardiogram to enhance cardiac monitoring during magnetic resonance imaging. Engineering Applications of Artificial Intelligence. 133. 108483–108483. 2 indexed citations
11.
12.
Chowdhury, Moajjem Hossain, et al.. (2024). Improving MRI Resolution: A Cycle Consistent Generative Adversarial Network-Based Approach for 3T to 7T Translation. IEEE Access. 12. 116498–116515. 4 indexed citations
13.
Sarraf, Masoud, Farayi Musharavati, Fadi Jaber, et al.. (2023). Anodization and nonstructural surface characterizations of fabricated Ti–29Nb–13Ta–7.1Zr alloy for biomedical applications and its mechanical, wettability, tribological, and corrosion properties. Materials Chemistry and Physics. 314. 128825–128825. 3 indexed citations
14.
Chowdhury, Muhammad E. H., Hany E. Marei, Mahbub Hassan, et al.. (2023). Oxygen releasing patches based on carbohydrate polymer and protein hydrogels for diabetic wound healing: A review. International Journal of Biological Macromolecules. 250. 126174–126174. 28 indexed citations
15.
Hosseini, Saleh, Amith Khandakar, Muhammad E. H. Chowdhury, et al.. (2022). Novel and robust machine learning approach for estimating the fouling factor in heat exchangers. Energy Reports. 8. 8767–8776. 35 indexed citations
16.
Rahman, Tawsifur, Alex Akinbi, Muhammad E. H. Chowdhury, et al.. (2022). COV-ECGNET: COVID-19 detection using ECG trace images with deep convolutional neural network. Health Information Science and Systems. 10(1). 1–1. 64 indexed citations
17.
Hossain, Md Shafayet, Mamun Bin Ibne Reaz, Muhammad E. H. Chowdhury, et al.. (2022). Motion Artifacts Correction From EEG and fNIRS Signals Using Novel Multiresolution Analysis. IEEE Access. 10. 29760–29777. 22 indexed citations
18.
Khandakar, Amith, Muhammad E. H. Chowdhury, Mamun Bin Ibne Reaz, et al.. (2022). A Novel Machine Learning Approach for Severity Classification of Diabetic Foot Complications Using Thermogram Images. Sensors. 22(11). 4249–4249. 39 indexed citations
19.
Rahman, Tawsifur, Amith Khandakar, Muhammad Abdul Kadir, et al.. (2020). Reliable Tuberculosis Detection Using Chest X-Ray With Deep Learning, Segmentation and Visualization. IEEE Access. 8. 191586–191601. 375 indexed citations breakdown →
20.
Chowdhury, Muhammad E. H., et al.. (2020). An Intelligent and Low-Cost Eye-Tracking System for Motorized Wheelchair Control. Sensors. 20(14). 3936–3936. 44 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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