Arif Khan

3.3k total citations · 1 hit paper
77 papers, 2.0k citations indexed

About

Arif Khan is a scholar working on Artificial Intelligence, Epidemiology and Computer Vision and Pattern Recognition. According to data from OpenAlex, Arif Khan has authored 77 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 13 papers in Epidemiology and 10 papers in Computer Vision and Pattern Recognition. Recurrent topics in Arif Khan's work include Chronic Disease Management Strategies (9 papers), Graph Theory and Algorithms (9 papers) and Machine Learning in Healthcare (7 papers). Arif Khan is often cited by papers focused on Chronic Disease Management Strategies (9 papers), Graph Theory and Algorithms (9 papers) and Machine Learning in Healthcare (7 papers). Arif Khan collaborates with scholars based in Australia, United Kingdom and United States. Arif Khan's co-authors include Shahadat Uddin, Md Ekramul Hossain, Mohammad Ali Moni, Uma Srinivasan, Mahantesh Halappanavar, Nahin Hussain, Louise A. Baur, Matloob Khushi, Alex Pothen and F Walker and has published in prestigious journals such as Journal of the American College of Cardiology, PLoS ONE and Scientific Reports.

In The Last Decade

Arif Khan

72 papers receiving 2.0k citations

Hit Papers

Comparing different supervised machine learning algorithm... 2019 2026 2021 2023 2019 250 500 750 1000

Peers

Arif Khan
Comparison fields: 5 of 194
  • Artificial Intelligence 566
  • Health Information Management 382
  • Epidemiology 239
  • Radiology, Nuclear Medicine and Imaging 230
  • Molecular Biology 207
Md Manjurul Ahsan United States
Leila Shahmoradi Iran
Guotong Xie China
Stephan Dreiseitl Austria
Gopi Battineni Italy
You Chen United States
Sanjay Purushotham United States
Lucia Sacchi Italy
Sooyoung Yoo South Korea
William J. Long United States
Md Manjurul Ahsan United States View profile →
Citations per field, relative to Arif Khan
Arif Khan · 1×
Citations per year, relative to Arif Khan
Arif Khan · 1×

Countries citing papers authored by Arif Khan

Since Specialization
Citations

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

Fields of papers citing papers by Arif Khan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Arif Khan

This figure shows the co-authorship network connecting the top 25 collaborators of Arif Khan. A scholar is included among the top collaborators of Arif 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 Arif Khan. Arif Khan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 2
2 5
3 11
4 5
5 61
6 17
7 46
8 45
9
Comparing different supervised machine learning algorithms for disease prediction breakdown →
1024
10 79
11 4
12 3
13
Journal of Rural Development & Administration: A Bibliometric Study
0
14 2
15 14
16 5
17 2
18 5
19 15
20 2

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.

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