Muhammad Kabir
Impact in
- Neurology top 1%
- Brain Tumor Detection and Classification
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- Advanced Neural Network Applications
Papers in
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- Machine Learning in Bioinformatics 29
- RNA and protein synthesis mechanisms 15
- Genomics and Phylogenetic Studies 11
- vaccines and immunoinformatics approaches 8
- Protein Structure and Dynamics 3
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- Computational Drug Discovery Methods 3
- Co-authors
- Saeed Ahmad (23 shared papers)Maqsood Hayat (9 shared papers)Zar Nawab Khan Swati (9 shared papers)Farman Ali (8 shared papers)Zakir Ali (7 shared papers)Jianfeng Lu (2 shared papers)Qinghua Zhao (2 shared papers)Dong‐Jun Yu (9 shared papers)
In The Last Decade
Muhammad Kabir
36 papers receiving 1.7k citations
Muhammad Kabir's Hit Papers
Peers
Comparison fields: 5 of 96
- Neurology 567
- Computer Vision and Pattern Recognition 492
- Microbiology 102
- Molecular Biology 939
- Radiology, Nuclear Medicine and Imaging 208
Countries citing papers authored by Muhammad Kabir
This map shows the geographic impact of Muhammad Kabir'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 Kabir with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Muhammad Kabir more than expected).
Fields of papers citing papers by Muhammad Kabir
This network shows the impact of papers produced by Muhammad Kabir. 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 Kabir. The network helps show where Muhammad Kabir may publish in the future.
Co-authors
The 25 scholars most cited alongside Muhammad Kabir, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Brain tumor classification for MR images using transfer learning and fine-tuning Hit paper breakdown → | 2019 | 580 |
| 2 | 2019 | 173 | |
| 3 | 2015 | 125 | |
| 4 | 2015 | 95 | |
| 5 | 2018 | 72 | |
| 6 | 2018 | 69 | |
| 7 | 2016 | 68 | |
| 8 | 2019 | 59 | |
| 9 | 2021 | 54 | |
| 10 | 2019 | 52 | |
| 11 | 2017 | 47 | |
| 12 | 2019 | 47 | |
| 13 | 2020 | 34 | |
| 14 | 2021 | 32 | |
| 15 | 2018 | 30 | |
| 16 | 2015 | 30 | |
| 17 | 2017 | 30 | |
| 18 | 2018 | 27 | |
| 19 | 2022 | 26 | |
| 20 | 2018 | 25 |
About Muhammad Kabir
Muhammad Kabir is a scholar working on Molecular Biology, Computational Theory and Mathematics, Microbiology, Infectious Diseases and Health Information Management, having authored 37 papers that have together received 1.8k indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (29 papers), RNA and protein synthesis mechanisms (15 papers), Genomics and Phylogenetic Studies (11 papers), vaccines and immunoinformatics approaches (8 papers), Antimicrobial Peptides and Activities (3 papers), Protein Structure and Dynamics (3 papers), Computational Drug Discovery Methods (3 papers) and Patient Safety and Medication Errors (2 papers). The work is most often cited by research in Neurology (567 citations), Computer Vision and Pattern Recognition (492 citations), Microbiology (102 citations), Molecular Biology (939 citations) and Radiology, Nuclear Medicine and Imaging (208 citations). Muhammad Kabir has collaborated with scholars based in Pakistan, China and Thailand. Frequent co-authors include Saeed Ahmad, Maqsood Hayat, Zar Nawab Khan Swati, Farman Ali, Zakir Ali, Jianfeng Lu, Qinghua Zhao, Dong‐Jun Yu, Muhammad Arif and Muhammad Iqbal. Their work appears in journals such as Chemometrics and Intelligent Laboratory Systems, Analytical Biochemistry, Computer Methods and Programs in Biomedicine, Genomics and IEEE/ACM Transactions on Computational Biology and Bioinformatics.
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.