Khalid Al‐Dasuqi

15 papers receiving 381 citations

Peers

Khalid Al‐Dasuqi
Comparison fields: 5 of 50
  • Health Informatics 12
  • Pulmonary and Respiratory Medicine 268
  • Cardiology and Cardiovascular Medicine 152
  • Neurology 82
  • Epidemiology 181
Replace Ryu Fukumitsu with:
Ryu Fukumitsu Japan
David Doig United Kingdom
Naomi Larsen Germany
M. Aleksic Germany
Karolina Saganiak Poland
Κωνσταντίνος Κούσκουρας Greece
Andrea Willfort Austria
Marion Boulanger France
Kévin Premat France
Anna Bayer-Karpinska Germany
Khalid Al‐Dasuqi relative to Ryu Fukumitsu Japan Ryu Fukumitsu's profile →
Citations per field
00.5×3.0×
Ryu Fukumitsu · 1×
Citations per year

Countries citing papers authored by Khalid Al‐Dasuqi

Since Specialization
Citations

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

Fields of papers citing papers by Khalid Al‐Dasuqi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Khalid Al‐Dasuqi. 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 Al‐Dasuqi. The network helps show where Khalid Al‐Dasuqi may publish in the future.

Co-authors

The 25 scholars most cited alongside Khalid Al‐Dasuqi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Khalid Al‐Dasuqi Line = papers co-authored together Khalid Al‐Dasuqi links everyone, so they are left out of the graph.

All Works

17 of 17 papers shown
#Work
1 201684
2 201772
3 201851
4 202043
5 201728
6 201923
7 201720
8 202219
9 202016
10 201712
11 20216
12 20214
13 20232
14 20232
15 20221
16 20220
17 20250

About Khalid Al‐Dasuqi

Khalid Al‐Dasuqi is a scholar working on Pulmonary and Respiratory Medicine, Epidemiology, Surgery, Neurology and Cardiology and Cardiovascular Medicine, having authored 17 papers that have together received 383 indexed citations. Recurring topics across this work include Acute Ischemic Stroke Management (6 papers), Cerebrovascular and Carotid Artery Diseases (6 papers), Sarcoma Diagnosis and Treatment (5 papers), Cardiovascular Health and Disease Prevention (3 papers), Vascular Malformations and Hemangiomas (3 papers), Soft tissue tumor case studies (2 papers), Artificial Intelligence in Healthcare and Education (2 papers) and Intracranial Aneurysms: Treatment and Complications (2 papers). The work is most often cited by research in Health Informatics (12 citations), Pulmonary and Respiratory Medicine (268 citations), Cardiology and Cardiovascular Medicine (152 citations), Neurology (82 citations) and Epidemiology (181 citations). Khalid Al‐Dasuqi has collaborated with scholars based in United States, United Kingdom and Norway. Frequent co-authors include Ajay Gupta, Hediyeh Baradaran, Hooman Kamel, Diana Delgado, Ashley E. Giambrone, Ashley Knight‐Greenfield, Gülce Askin, Michele H. Johnson, Praneil Patel and Gino Gialdini. Their work appears in journals such as Skeletal Radiology, American Journal of Neuroradiology, Journal of the American Heart Association, Stroke and Radiographics.

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.

Explore authors with similar magnitude of impact