M. Jamal Deen

1.0k total citations · 1 hit paper
8 papers, 617 citations indexed

About

M. Jamal Deen is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, M. Jamal Deen has authored 8 papers receiving a total of 617 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 2 papers in Computer Vision and Pattern Recognition and 2 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in M. Jamal Deen's work include ECG Monitoring and Analysis (1 paper), Big Data and Business Intelligence (1 paper) and Diabetic Foot Ulcer Assessment and Management (1 paper). M. Jamal Deen is often cited by papers focused on ECG Monitoring and Analysis (1 paper), Big Data and Business Intelligence (1 paper) and Diabetic Foot Ulcer Assessment and Management (1 paper). M. Jamal Deen collaborates with scholars based in Canada and China. M. Jamal Deen's co-authors include Laurence T. Yang, Xiaokang Wang, Qingchen Zhang, Hang Yu, David Armstrong, Xia Xie, Abu Ilius Faisal, Qingxia Zhang, Mahdi Naghshvarianjahromi and Shiva Kumar and has published in prestigious journals such as IEEE Access, IEEE Communications Magazine and Sensors.

In The Last Decade

M. Jamal Deen

7 papers receiving 599 citations

Hit Papers

Convolutional neural networks for medical image analysis:... 2021 2026 2022 2024 2021 50 100 150 200

Peers

M. Jamal Deen
Comparison fields: 5 of 117
  • Artificial Intelligence 204
  • Computer Vision and Pattern Recognition 153
  • Computer Networks and Communications 142
  • Information Systems 104
  • Radiology, Nuclear Medicine and Imaging 98
H. Khanna Nehemiah India
Daniel Sierra-Sosa United States
Gokulnath Chandra Babu India
Suneet Gupta India
A. Balasundaram India
Haya Alaskar Saudi Arabia
Gelan Yang China
Rodrigo Olivares Chile
Mehmet Fatih Akay Türkiye
Yunbo Rao China
H. Khanna Nehemiah India View profile →
Citations per field, relative to M. Jamal Deen
M. Jamal Deen · 1×
Citations per year, relative to M. Jamal Deen
M. Jamal Deen · 1×

Countries citing papers authored by M. Jamal Deen

Since Specialization
Citations

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

Fields of papers citing papers by M. Jamal Deen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M. Jamal Deen. 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 M. Jamal Deen. The network helps show where M. Jamal Deen may publish in the future.

Co-authorship network of co-authors of M. Jamal Deen

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

All Works

8 of 8 papers shown
# Work Indexed citations
1 0
2 58
3
Convolutional neural networks for medical image analysis: State-of-the-art, comparisons, improvement and perspectives breakdown →
240
4 21
5 12
6 56
7 9
8 221

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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2026