Sean M. Siebert

2.7k citations
12 papers · 746 · h-index 8

Impact in

    • Silk-based biomaterials and applications
    • Electrospun Nanofibers in Biomedical Applications
    • Advanced Sensor and Energy Harvesting Materials
    • Plasmonic and Surface Plasmon Research
    • Biosensors and Analytical Detection

Papers in

Sean M. Siebert

12 papers receiving 731 citations

Peers

Sean M. Siebert
Comparison fields: 5 of 96
  • Biomaterials 204
  • Biomedical Engineering 419
  • Health Informatics 12
  • Electronic, Optical and Magnetic Materials 140
  • Polymers and Plastics 92
Replace Seung Ho Choi with:
Seung Ho Choi South Korea
Ugur Bozuyuk Türkiye
Yun Jung Heo South Korea
Cody Cleveland United States
Zhuang Hao China
Jérôme Charmet United Kingdom
Martha E. Grady United States
Ian Trase United States
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Sean M. Siebert relative to Seung Ho Choi South Korea Seung Ho Choi's profile →
Citations per field
00.5×3.2×
Seung Ho Choi · 1×
Citations per year

Countries citing papers authored by Sean M. Siebert

Since Specialization
Citations

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

Fields of papers citing papers by Sean M. Siebert

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sean M. Siebert. 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 Sean M. Siebert. The network helps show where Sean M. Siebert may publish in the future.

Co-authors

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

All Works

12 of 12 papers shown
#Work
1 2012326
2 2011215
3 201298
4 202157
5 201021
6 20207
7 20187
8 20207
9
Toward Automated Pre-Biopsy Thyroid Cancer Risk Estimation in Ultrasound.
20172
10 20182
11 20122
12 20122

About Sean M. Siebert

Sean M. Siebert is a scholar working on Biomaterials, Radiology, Nuclear Medicine and Imaging, Endocrinology, Diabetes and Metabolism, Biomedical Engineering and Molecular Biology, having authored 12 papers that have together received 746 indexed citations. Recurring topics across this work include Thyroid Cancer Diagnosis and Treatment (4 papers), Radiomics and Machine Learning in Medical Imaging (4 papers), Silk-based biomaterials and applications (4 papers), Head and Neck Anomalies (2 papers), Advanced Chemical Sensor Technologies (1 paper), Lung Cancer Diagnosis and Treatment (1 paper), COVID-19 diagnosis using AI (1 paper) and Advanced biosensing and bioanalysis techniques (1 paper). The work is most often cited by research in Biomaterials (204 citations), Biomedical Engineering (419 citations), Health Informatics (12 citations), Electronic, Optical and Magnetic Materials (140 citations) and Polymers and Plastics (92 citations). Sean M. Siebert has collaborated with scholars based in United States, South Korea and Israel. Frequent co-authors include Fiorenzo G. Omenetto, David L. Kaplan, Mark A. Brenckle, Richard D. Averitt, Mengkun Liu, Hu Tao, Miaomiao Yang, Michael C. McAlpine, John A. Rogers and Manu Sebastian Mannoor. Their work appears in journals such as Advanced Materials, American Journal of Roentgenology, European Radiology, European Journal of Radiology and Applied Physics Letters.

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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