Muhammad Sharif
- Artificial Intelligence top 1%
- Computer Vision and Pattern Recognition top 1%
- Radiology, Nuclear Medicine and Imaging top 2%
- Oncology top 5%
- Neurology top 5%
- Co-authors
- Muhammad Attique KhanMussarat YasminTallha AkramAmjad RehmanTanzila SabaSteven Lawrence FernandesMuhammad Younus JavedFarhat Afza
- Topics
- Retinal Imaging and Analysis (9 papers)COVID-19 diagnosis using AI (9 papers)Cutaneous Melanoma Detection and Management (8 papers)
- Cited by
- Computer Vision and Pattern RecognitionRadiology, Nuclear Medicine and ImagingGastroenterology
- Journals
- SHILAP Revista de lepidopterologíaApplied Soft ComputingMethods
- Partner nations
- PakistanSaudi ArabiaIndia
In The Last Decade
Muhammad Sharif
43 papers receiving 2.4k citations
Peers
Comparison fields: 5 of 119
- Artificial Intelligence 947
- Computer Vision and Pattern Recognition 928
- Radiology, Nuclear Medicine and Imaging 874
- Oncology 591
- Neurology 265
Countries citing papers authored by Muhammad Sharif
This map shows the geographic impact of Muhammad Sharif'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 Sharif with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Muhammad Sharif more than expected).
Fields of papers citing papers by Muhammad Sharif
This network shows the impact of papers produced by Muhammad Sharif. 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 Sharif. The network helps show where Muhammad Sharif may publish in the future.
Co-authorship network of co-authors of Muhammad Sharif
This figure shows the co-authorship network connecting the top 25 collaborators of Muhammad Sharif. A scholar is included among the top collaborators of Muhammad Sharif 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 Sharif. Muhammad Sharif is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 51 | |
| 3 | 85 | |
| 4 | 25 | |
| 5 | 4 | |
| 6 | 104 | |
| 7 | 185 | |
| 8 | 68 | |
| 9 | 33 | |
| 10 | 31 | |
| 11 | 59 | |
| 12 | 83 | |
| 13 | 45 | |
| 14 | 59 | |
| 15 | 41 | |
| 16 | 55 | |
| 17 | 55 | |
| 18 | 75 | |
| 19 | 56 | |
| 20 | 13 |
About Muhammad Sharif
Muhammad Sharif is a scholar working on Gastroenterology, Ophthalmology and Radiology, Nuclear Medicine and Imaging, having authored 44 papers that have together received 2.6k indexed citations. Recurring topics across this work include Retinal Imaging and Analysis (9 papers), COVID-19 diagnosis using AI (9 papers) and Cutaneous Melanoma Detection and Management (8 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (928 citations), Radiology, Nuclear Medicine and Imaging (874 citations) and Gastroenterology (184 citations). Muhammad Sharif has collaborated with scholars based in Pakistan, Saudi Arabia and India. Frequent co-authors include Muhammad Attique Khan, Mussarat Yasmin, Tallha Akram, Amjad Rehman, Tanzila Saba, Steven Lawrence Fernandes, Muhammad Younus Javed, Farhat Afza, Mudassar Raza and Jamal Hussain Shah. Their work appears in journals such as SHILAP Revista de lepidopterología, Applied Soft Computing and Methods.
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.