Muhammad Farhan Khan
- Artificial Intelligence top 5%
- Computer Networks and Communications top 10%
- Health Information Management top 1%
- Radiology, Nuclear Medicine and Imaging top 10%
- Electrical and Electronic Engineering
- Co-authors
- Muhammad Adnan KhanAtta RahmanTaher M. GhazalMunir AhmadSaad QaisarSalman AliGhassan F. IssaUsama Ahmed
- Topics
- AI in cancer detection (9 papers)COVID-19 diagnosis using AI (7 papers)Advanced MIMO Systems Optimization (6 papers)
- Journals
- SHILAP Revista de lepidopterologíaScientific ReportsIEEE Access
- Partner nations
- PakistanUnited Arab EmiratesSaudi Arabia
In The Last Decade
Muhammad Farhan Khan
47 papers receiving 679 citations
Hit Papers
Peers
Comparison fields: 5 of 120
- Artificial Intelligence 267
- Computer Networks and Communications 164
- Health Information Management 141
- Radiology, Nuclear Medicine and Imaging 135
- Electrical and Electronic Engineering 112
Countries citing papers authored by Muhammad Farhan Khan
This map shows the geographic impact of Muhammad Farhan Khan'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 Farhan Khan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Muhammad Farhan Khan more than expected).
Fields of papers citing papers by Muhammad Farhan Khan
This network shows the impact of papers produced by Muhammad Farhan Khan. 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 Farhan Khan. The network helps show where Muhammad Farhan Khan may publish in the future.
Co-authorship network of co-authors of Muhammad Farhan Khan
This figure shows the co-authorship network connecting the top 25 collaborators of Muhammad Farhan Khan. A scholar is included among the top collaborators of Muhammad Farhan Khan 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 Farhan Khan. Muhammad Farhan Khan 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 | 0 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 2 | |
| 6 | 1 | |
| 7 | 2 | |
| 8 | 2 | |
| 9 | 4 | |
| 10 | 7 | |
| 11 | 5 | |
| 12 | 0 | |
| 13 | 15 | |
| 14 | 34 | |
| 15 | Prediction of Diabetes Empowered With Fused Machine Learningbreakdown → | 154 |
| 16 | 78 | |
| 17 | 1 | |
| 18 | 5 | |
| 19 | 7 | |
| 20 | 2 |
About Muhammad Farhan Khan
Muhammad Farhan Khan is a scholar working on Health Informatics, Health Information Management and Computer Vision and Pattern Recognition, having authored 54 papers that have together received 742 indexed citations. Recurring topics across this work include AI in cancer detection (9 papers), COVID-19 diagnosis using AI (7 papers) and Advanced MIMO Systems Optimization (6 papers). The work is most often cited by research in Health Information Management (141 citations), Artificial Intelligence (267 citations) and Computer Networks and Communications (164 citations). Muhammad Farhan Khan has collaborated with scholars based in Pakistan, United Arab Emirates and Saudi Arabia. Frequent co-authors include Muhammad Adnan Khan, Atta Rahman, Taher M. Ghazal, Munir Ahmad, Saad Qaisar, Salman Ali, Ghassan F. Issa, Usama Ahmed, Shabib Aftab and Muhammad Naeem. Their work appears in journals such as SHILAP Revista de lepidopterología, Scientific Reports and IEEE Access.
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.