Mobarakol Islam

1.8k citations
46 papers · 407 · h-index 13

Impact in

Papers in

Mobarakol Islam

42 papers receiving 400 citations

Peers

Mobarakol Islam
Comparison fields: 5 of 68
  • Health Informatics 24
  • Computer Vision and Pattern Recognition 124
  • Neurology 46
  • Radiology, Nuclear Medicine and Imaging 94
  • Artificial Intelligence 116
Replace Neeraj Sharma with:
Neeraj Sharma India
Yonghong Shi China
D. R. Sarvamangala India
Nandhini Santhanam Germany
Zhennan Yan United States
Zelong Liu China
Shanhui Sun United States
Mahboubeh Jannesari Germany
Hans Meine Germany
Xuanang Xu United States
Mobarakol Islam relative to Neeraj Sharma India Neeraj Sharma's profile →
Citations per field
00.5×
Neeraj Sharma · 1×
Citations per year

Countries citing papers authored by Mobarakol Islam

Since Specialization
Citations

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

Fields of papers citing papers by Mobarakol Islam

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Mobarakol Islam, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Mobarakol Islam Line = papers co-authored together Mobarakol Islam links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 46 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202147
2 202132
3 202031
4 202030
5 202026
6 202423
7 202221
8 202120
9 201716
10 202316
11 202313
12 202412
13 201812
14 202411
15 20248
16 20127
17 20247
18 20246
19 20216
20 20116

About Mobarakol Islam

Mobarakol Islam is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Biomedical Engineering, Radiology, Nuclear Medicine and Imaging and Surgery, having authored 46 papers that have together received 407 indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (10 papers), Multimodal Machine Learning Applications (7 papers), Neural Networks and Applications (6 papers), Advanced Neural Network Applications (5 papers), Surgical Simulation and Training (4 papers), Radiomics and Machine Learning in Medical Imaging (4 papers), Anatomy and Medical Technology (4 papers) and Artificial Intelligence in Healthcare and Education (4 papers). The work is most often cited by research in Health Informatics (24 citations), Computer Vision and Pattern Recognition (124 citations), Neurology (46 citations), Radiology, Nuclear Medicine and Imaging (94 citations) and Artificial Intelligence (116 citations). Mobarakol Islam has collaborated with scholars based in United Kingdom, Hong Kong and Singapore. Frequent co-authors include Hongliang Ren, Chwee Ming Lim, Mengya Xu, Long Bai, Dulani Meedeniya, Indika Perera, Vibashan VS, An Wang, Beilei Cui and Weng Kin Wong. Their work appears in journals such as International Journal of Computer Assisted Radiology and Surgery, Medical Image Analysis, IEEE Robotics and Automation Letters, IEEE Transactions on Medical Imaging and Information Fusion.

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.

Explore authors with similar magnitude of impact