Shayan Shams

39 papers receiving 736 citations

Peers

Shayan Shams
Comparison fields: 5 of 125
  • Oral Surgery 103
  • Health Informatics 21
  • General Dentistry 14
  • Internal Medicine 27
  • Periodontics 34
Replace Marı́a J. Carreira with:
Marı́a J. Carreira Spain
Kyu-Hwan Jung South Korea
Yongwon Cho South Korea
D. R. Sarvamangala India
Avi Ben-Cohen Israel
Muthu Subash Kavitha Japan
Jai Prashanth Rao Singapore
Yuchen Xie China
Justin Ker Singapore
Shayan Shams relative to Marı́a J. Carreira Spain Marı́a J. Carreira's profile →
Citations per field
00.5×
Marı́a J. Carreira · 1×
Citations per year

Countries citing papers authored by Shayan Shams

Since Specialization
Citations

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

Fields of papers citing papers by Shayan Shams

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 42 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202199
2 201897
3 201766
4 201745
5 201844
6 202242
7 202233
8 202332
9 202230
10 199629
11 200227
12 202220
13 202220
14 199520
15
Experimental design, analysis of variance and slide quality assessment in gene expression arrays.
200118
16 200217
17 202316
18 202115
19 202013
20 201812

About Shayan Shams

Shayan Shams is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Molecular Biology, Epidemiology and Electrical and Electronic Engineering, having authored 42 papers that have together received 759 indexed citations. Recurring topics across this work include Neural Networks and Applications (5 papers), Gene expression and cancer classification (5 papers), Radiomics and Machine Learning in Medical Imaging (5 papers), Advanced Memory and Neural Computing (4 papers), Ferroelectric and Negative Capacitance Devices (3 papers), Public Relations and Crisis Communication (3 papers), AI in cancer detection (3 papers) and Dental Radiography and Imaging (3 papers). The work is most often cited by research in Oral Surgery (103 citations), Health Informatics (21 citations), General Dentistry (14 citations), Internal Medicine (27 citations) and Periodontics (34 citations). Shayan Shams has collaborated with scholars based in United States, South Korea and Saudi Arabia. Frequent co-authors include Kisung Lee, Xiaoqian Jiang, Seung‐Jong Park, Seungwon Yang, Chun‐Teh Lee, Charles M. Higgins, Sean I. Savitz, Michelle A. Meyer, Lei Zou and Nina Lam. Their work appears in journals such as BMC Medical Informatics and Decision Making, Scientific Reports, BMC Oral Health, Nature Communications and Frontiers in Bioengineering and Biotechnology.

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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