Rafid Mostafiz

519 total citations
29 papers, 315 citations indexed

About

Rafid Mostafiz is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Rafid Mostafiz has authored 29 papers receiving a total of 315 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Computer Vision and Pattern Recognition, 13 papers in Artificial Intelligence and 7 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Rafid Mostafiz's work include AI in cancer detection (7 papers), Radiomics and Machine Learning in Medical Imaging (5 papers) and COVID-19 diagnosis using AI (5 papers). Rafid Mostafiz is often cited by papers focused on AI in cancer detection (7 papers), Radiomics and Machine Learning in Medical Imaging (5 papers) and COVID-19 diagnosis using AI (5 papers). Rafid Mostafiz collaborates with scholars based in Bangladesh, United States and Australia. Rafid Mostafiz's co-authors include Mohammad Shorif Uddin, Mohammad Motiur Rahman, Khandaker Mohammad Mohi Uddin, Md. Mahfuz Reza, Bikash Kumar Paul, Samrat Kumar Dey, Imran Hossain, Mohammad M. Rahman, Md. Mahmodul Hasan and Md. Ariful Islam and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

In The Last Decade

Rafid Mostafiz

25 papers receiving 311 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Rafid Mostafiz Bangladesh 12 150 112 90 43 37 29 315
Hung N. Pham Vietnam 8 145 1.0× 120 1.1× 57 0.6× 83 1.9× 22 0.6× 19 365
G. Ramkumar India 9 97 0.6× 80 0.7× 59 0.7× 20 0.5× 12 0.3× 66 422
Sofia Zahia Spain 8 170 1.1× 127 1.1× 81 0.9× 9 0.2× 98 2.6× 12 406
Haseeb Hassan China 13 93 0.6× 166 1.5× 151 1.7× 12 0.3× 30 0.8× 45 514
Yanda Meng United Kingdom 11 252 1.7× 227 2.0× 230 2.6× 17 0.4× 12 0.3× 28 504
Megha Bhushan India 14 200 1.3× 135 1.2× 65 0.7× 112 2.6× 13 0.4× 39 488
Cristián Castillo-Olea Spain 8 189 1.3× 174 1.6× 56 0.6× 96 2.2× 5 0.1× 19 371
Hamada R. H. Al-Absi Qatar 11 99 0.7× 170 1.5× 34 0.4× 106 2.5× 14 0.4× 30 390
Alexandr A. Kalinin United States 10 98 0.7× 93 0.8× 74 0.8× 17 0.4× 8 0.2× 16 384
Rajeshwar Dass India 9 131 0.9× 136 1.2× 164 1.8× 9 0.2× 39 1.1× 28 394

Countries citing papers authored by Rafid Mostafiz

Since Specialization
Citations

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

Fields of papers citing papers by Rafid Mostafiz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Rafid Mostafiz. 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 Rafid Mostafiz. The network helps show where Rafid Mostafiz may publish in the future.

Co-authorship network of co-authors of Rafid Mostafiz

This figure shows the co-authorship network connecting the top 25 collaborators of Rafid Mostafiz. A scholar is included among the top collaborators of Rafid Mostafiz 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 Rafid Mostafiz. Rafid Mostafiz 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.
Mostafiz, Rafid, et al.. (2025). Exploring Multimodal Framework of Optimized Feature-Based Machine Learning to Revolutionize the Diagnosis of Parkinson’s Disease: AI-Driven Insights. Biomedical Materials & Devices. 4(1). 605–624. 3 indexed citations
2.
Uddin, Muhammad Shahin, et al.. (2025). An explainable and federated deep learning framework for skin cancer diagnosis. PLoS ONE. 20(7). e0324393–e0324393.
3.
Hasan, Md. Mehedi, et al.. (2025). NeuroYOLO: A Lightweight YOLOv10-MobileNetV3 Framework for Real-Time Brain Tumor Detection in MRI Scans. Biomedical Materials & Devices.
4.
5.
6.
Uddin, Khandaker Mohammad Mohi, et al.. (2025). Explainable Machine Learning for Phishing Site Detection: A High‐Efficiency Approach Using Boosting Models and SHAP. The Journal of Engineering. 2025(1). 1 indexed citations
7.
Mostafiz, Rafid, et al.. (2024). Deep learning-based edge detection for random natural images. SHILAP Revista de lepidopterología. 5(1). 100183–100183. 3 indexed citations
8.
Uddin, Khandaker Mohammad Mohi, et al.. (2024). An ensemble machine learning-based approach to predict thyroid disease using hybrid feature selection. SHILAP Revista de lepidopterología. 1(3). 229–239.
9.
Mostafiz, Rafid, et al.. (2024). XAI-FusionNet: Diabetic foot ulcer detection based on multi-scale feature fusion with explainable artificial intelligence. Heliyon. 10(10). e31228–e31228. 20 indexed citations
10.
Mostafiz, Rafid, et al.. (2024). DFU_XAI: A Deep Learning-Based Approach to Diabetic Foot Ulcer Detection Using Feature Explainability. Biomedical Materials & Devices. 2(2). 1225–1245. 17 indexed citations
11.
Uddin, Khandaker Mohammad Mohi, et al.. (2024). An ensemble machine learning-based approach to predict cervical cancer using hybrid feature selection. SHILAP Revista de lepidopterología. 4(3). 100169–100169. 17 indexed citations
12.
Uddin, Khandaker Mohammad Mohi, et al.. (2023). XML-GBM lung: An explainable machine learning-based application for the diagnosis of lung cancer. Journal of Pathology Informatics. 14. 100307–100307. 20 indexed citations
13.
Mostafiz, Rafid, et al.. (2023). DFU_MultiNet: A deep neural network approach for detecting diabetic foot ulcers through multi-scale feature fusion using the DFU dataset. Intelligence-Based Medicine. 8. 100128–100128. 15 indexed citations
14.
Uddin, Khandaker Mohammad Mohi, Samrat Kumar Dey, Hafiz Md. Hasan Babu, et al.. (2022). Feature fusion based VGGFusionNet model to detect COVID-19 patients utilizing computed tomography scan images. Scientific Reports. 12(1). 21796–21796. 6 indexed citations
15.
Uddin, Khandaker Mohammad Mohi, et al.. (2022). Smart Home Security Using Facial Authentication and Mobile Application. International Journal of Wireless and Microwave Technologies. 12(2). 40–50. 6 indexed citations
16.
Mostafiz, Rafid, et al.. (2020). Covid-19 detection in chest X-ray through random forest classifier using a hybridization of deep CNN and DWT optimized features. Journal of King Saud University - Computer and Information Sciences. 34(6). 3226–3235. 61 indexed citations
17.
Mostafiz, Rafid, et al.. (2019). An intelligent system for gastrointestinal polyp detection in endoscopic video using fusion of bidimensional empirical mode decomposition and convolutional neural network features. International Journal of Imaging Systems and Technology. 30(1). 224–233. 18 indexed citations
18.
Islam, Mohammad Ashraful, et al.. (2018). Speckle noise reduction for 3D ultrasound images by optimum threshold parameter estimation of bi-dimensional empirical mode decomposition using Fisher discriminant analysis. International Journal of Signal and Imaging Systems Engineering. 11(2). 93–93. 2 indexed citations
19.
Mostafiz, Rafid, et al.. (2018). Speckle noise reduction for 3D ultrasound images by optimum threshold parameter estimation of bi-dimensional empirical mode decomposition using Fisher discriminant analysis. International Journal of Signal and Imaging Systems Engineering. 11(2). 93–93. 5 indexed citations
20.
Mostafiz, Rafid, et al.. (2017). Speckle Noise Reduction for 3-D Ultrasound Images by Optimum Threshold Parameter Estimation of Wavelet Coefficients Using Fisher Discriminant Analysis. 17(4). 73–88. 2 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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