Khalid Masood Khan
- Artificial Intelligence top 10%
- Neurology top 10%
- Radiology, Nuclear Medicine and Imaging
- Computer Vision and Pattern Recognition top 10%
- Computer Networks and Communications
- Co-authors
- Mohammed A. Al GhamdiMuhammad Adnan KhanSultan H. AlmotiriMuzammil HussainSuhail Ashfaq ButtMuhammad Waqas NadeemAbdur RehmanSagheer Abbas
- Topics
- Machine Learning and ELM (3 papers)COVID-19 epidemiological studies (2 papers)COVID-19 diagnosis using AI (2 papers)
- Journals
- Brain SciencesComputers, materials & continua/Computers, materials & continua (Print)Indian Journal of Ophthalmology
- Partner nations
- Saudi ArabiaPakistanIndia
In The Last Decade
Khalid Masood Khan
10 papers receiving 283 citations
Peers
Comparison fields: 5 of 81
- Artificial Intelligence 120
- Neurology 111
- Radiology, Nuclear Medicine and Imaging 97
- Computer Vision and Pattern Recognition 92
- Computer Networks and Communications 52
Countries citing papers authored by Khalid Masood Khan
This map shows the geographic impact of Khalid Masood 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 Khalid Masood Khan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Khalid Masood Khan more than expected).
Fields of papers citing papers by Khalid Masood Khan
This network shows the impact of papers produced by Khalid Masood 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 Khalid Masood Khan. The network helps show where Khalid Masood Khan may publish in the future.
Co-authorship network of co-authors of Khalid Masood Khan
This figure shows the co-authorship network connecting the top 25 collaborators of Khalid Masood Khan. A scholar is included among the top collaborators of Khalid Masood 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 Khalid Masood Khan. Khalid Masood 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 | 6 | |
| 2 | 31 | |
| 3 | 43 | |
| 4 | 7 | |
| 5 | 16 | |
| 6 | 4 | |
| 7 | 18 | |
| 8 | 175 | |
| 9 | 20 | |
| 10 | 1 |
About Khalid Masood Khan
Khalid Masood Khan is a scholar working on Health Informatics, Modeling and Simulation and Health Information Management, having authored 10 papers that have together received 321 indexed citations. Recurring topics across this work include Machine Learning and ELM (3 papers), COVID-19 epidemiological studies (2 papers) and COVID-19 diagnosis using AI (2 papers). The work is most often cited by research in Neurology (111 citations), Health Informatics (9 citations) and Health Information Management (24 citations). Khalid Masood Khan has collaborated with scholars based in Saudi Arabia, Pakistan and India. Frequent co-authors include Mohammed A. Al Ghamdi, Muhammad Adnan Khan, Sultan H. Almotiri, Muzammil Hussain, Suhail Ashfaq Butt, Muhammad Waqas Nadeem, Abdur Rehman, Sagheer Abbas, Atta Rahman and Fahd Alhaidari. Their work appears in journals such as Brain Sciences, Computers, materials & continua/Computers, materials & continua (Print) and Indian Journal of Ophthalmology.
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.