Dong Yeob Shin
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- Thyroid Cancer Diagnosis and Treatment 37
- Thyroid Disorders and Treatments 16
- Pituitary Gland Disorders and Treatments 12
- Growth Hormone and Insulin-like Growth Factors 5
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- Ophthalmology and Eye Disorders 9
- Vitamin D Research Studies 4
- Nutrition and Dietetics top 10%
- Ophthalmology top 10%
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- Thyroid and Parathyroid Surgery 5
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- Radiomics and Machine Learning in Medical Imaging 4
Dong Yeob Shin
65 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 109
- Endocrinology, Diabetes and Metabolism 731
- Pathology and Forensic Medicine 299
- Nutrition and Dietetics 134
- Ophthalmology 57
- Cancer Research 94
Countries citing papers authored by Dong Yeob Shin
This map shows the geographic impact of Dong Yeob Shin'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 Dong Yeob Shin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dong Yeob Shin more than expected).
Fields of papers citing papers by Dong Yeob Shin
This network shows the impact of papers produced by Dong Yeob Shin. 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 Dong Yeob Shin. The network helps show where Dong Yeob Shin may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Dong Yeob Shin, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2024 | 1 | |
| 3 | 2023 | 3 | |
| 4 | 2022 | 33 | |
| 5 | 2020 | 35 | |
| 6 | 2019 | 27 | |
| 7 | 2019 | 1 | |
| 8 | 2019 | 21 | |
| 9 | 2019 | 20 | |
| 10 | 2019 | 9 | |
| 11 | 2019 | 21 | |
| 12 | 2018 | 38 | |
| 13 | 2016 | 49 | |
| 14 | 러시아의 정부와 국영에너지기업 관계 연구 : 로스네프트의 사례를 중심으로 | 2015 | 1 |
| 15 | 2015 | 49 | |
| 16 | 2014 | 7 | |
| 17 | 2014 | 70 | |
| 18 | 2014 | 2 | |
| 19 | 비계약업종의 이탈관리전략을 위한 상대적 이탈정의 모형 개발 | 2012 | 0 |
| 20 | Adam Brandenberger and Barry Nalebuff, Co-opetition | 1996 | 0 |
About Dong Yeob Shin
Dong Yeob Shin is a scholar working on Endocrinology, Diabetes and Metabolism, General Energy, Pathology and Forensic Medicine, Oncology and Nutrition and Dietetics, having authored 74 papers that have together received 1.3k indexed citations. Recurring topics across this work include Thyroid Cancer Diagnosis and Treatment (37 papers), Thyroid Disorders and Treatments (16 papers), Pituitary Gland Disorders and Treatments (12 papers), Ophthalmology and Eye Disorders (9 papers), Growth Hormone and Insulin-like Growth Factors (5 papers), Thyroid and Parathyroid Surgery (5 papers), Vitamin D Research Studies (4 papers) and Radiomics and Machine Learning in Medical Imaging (4 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (731 citations), Pathology and Forensic Medicine (299 citations), Nutrition and Dietetics (134 citations), Ophthalmology (57 citations) and Cancer Research (94 citations). Dong Yeob Shin has collaborated with scholars based in South Korea, United States and United Kingdom. Frequent co-authors include Eun Jig Lee, Jong Ho Lee, Sena Hwang, Jin Sook Yoon, Jung Hyun Kwak, Kwang Joon Kim, Daham Kim, Sun Young Jang, Woong Youn Chung and Hyeon Yeong Ahn. Their work appears in journals such as Thyroid, Medicine, Head & Neck, Journal of Clinical Medicine and PLoS ONE.
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.