Shan Ali

45 papers receiving 598 citations

Peers

Shan Ali
Comparison fields: 5 of 107
  • Health 70
  • General Health Professions 183
  • Health Informatics 9
  • Radiology, Nuclear Medicine and Imaging 81
  • Modeling and Simulation 14
Replace Jamie Chang with:
Jamie Chang United States
Ayako Hino Japan
Federica Ferrari Italy
Clareece R. Nevill United Kingdom
Lesley McGregor United Kingdom
Elvan C. Daniels United States
Lisa Di Prospero Canada
Megan C. Roberts United States
Neha Patel United States
Mrinalini Dey United Kingdom
Shan Ali relative to Jamie Chang United States Jamie Chang's profile →
Citations per field
00.5×1.5×1.9×
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Citations per year

Countries citing papers authored by Shan Ali

Since Specialization
Citations

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

Fields of papers citing papers by Shan Ali

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Shan Ali, 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 Shan Ali Line = papers co-authored together Shan Ali links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 49 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202089
2
Mammoscintigraphy with technetium-99m-sestamibi in suspected breast cancer.
199687
3 202062
4 202053
5 202049
6 202035
7 202030
8 202027
9 202123
10 202218
11 202116
12 201413
13 201413
14 202010
15 20217
16 20216
17 20206
18 20196
19
Skeletal scintigraphy with technetium-99m-tetraphenyl porphyrin sulfonate for the detection and determination of osteomyelitis in an animal model.
19976
20 20245

About Shan Ali

Shan Ali is a scholar working on General Health Professions, Surgery, Molecular Biology, Neurology and Pulmonary and Respiratory Medicine, having authored 49 papers that have together received 616 indexed citations. Recurring topics across this work include Health Literacy and Information Accessibility (9 papers), Pain Management and Treatment (2 papers), Black Holes and Theoretical Physics (2 papers), Moyamoya disease diagnosis and treatment (2 papers), Glycosylation and Glycoproteins Research (2 papers), Cosmology and Gravitation Theories (2 papers), Data-Driven Disease Surveillance (2 papers) and Misinformation and Its Impacts (2 papers). The work is most often cited by research in Health (70 citations), General Health Professions (183 citations), Health Informatics (9 citations), Radiology, Nuclear Medicine and Imaging (81 citations) and Modeling and Simulation (14 citations). Shan Ali has collaborated with scholars based in Poland, United States and Pakistan. Frequent co-authors include Tomasz Szmuda, Paweł Słoniewski, Akshita Singh, FERNANDO CESANI, Daniel F. Cowan, Javier Villanueva‐Meyer, Morton H. Leonard, Jacek Jassem, Renata Duchnowska and Neil Patel. Their work appears in journals such as World Neurosurgery, Clinical Neurology and Neurosurgery, Cancers, Journal of Medical Internet Research and Cerebrovascular Diseases.

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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