Shir‐Hwa Ueng
- Oncology top 5%
- Pulmonary and Respiratory Medicine top 5%
- Pathology and Forensic Medicine top 5%
- Cancer Research top 5%
- Radiology, Nuclear Medicine and Imaging top 5%
- Co-authors
- Fattaneh A. TavassoliYun‐Chung CheungYung‐Feng LoChuen HsuehShin‐Cheh ChenHsiu-Pei TsaiKai‐Ping ChangSheng‐Po Hao
- Topics
- Breast Cancer Treatment Studies (13 papers)Breast Lesions and Carcinomas (13 papers)AI in cancer detection (10 papers)
- Partner nations
- TaiwanUnited StatesUnited Kingdom
In The Last Decade
Shir‐Hwa Ueng
76 papers receiving 1.7k citations
Peers
Comparison fields: 5 of 100
- Oncology 459
- Pulmonary and Respiratory Medicine 427
- Pathology and Forensic Medicine 424
- Cancer Research 408
- Radiology, Nuclear Medicine and Imaging 392
Countries citing papers authored by Shir‐Hwa Ueng
This map shows the geographic impact of Shir‐Hwa Ueng'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 Shir‐Hwa Ueng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shir‐Hwa Ueng more than expected).
Fields of papers citing papers by Shir‐Hwa Ueng
This network shows the impact of papers produced by Shir‐Hwa Ueng. 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 Shir‐Hwa Ueng. The network helps show where Shir‐Hwa Ueng may publish in the future.
Co-authorship network of co-authors of Shir‐Hwa Ueng
This figure shows the co-authorship network connecting the top 25 collaborators of Shir‐Hwa Ueng. A scholar is included among the top collaborators of Shir‐Hwa Ueng based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Shir‐Hwa Ueng. Shir‐Hwa Ueng is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 1 | |
| 3 | 3 | |
| 4 | 38 | |
| 5 | 4 | |
| 6 | 37 | |
| 7 | 41 | |
| 8 | 18 | |
| 9 | 7 | |
| 10 | Phosphorylated mTOR expression correlates with podoplanin expression and high tumor grade in esophageal squamous cell carcinoma. | 9 |
| 11 | 25 | |
| 12 | 6 | |
| 13 | Phosphorylated mTOR expression correlates with poor outcome in early-stage triple negative breast carcinomas. | 60 |
| 14 | 14 | |
| 15 | 1 | |
| 16 | 57 | |
| 17 | 33 | |
| 18 | 15 | |
| 19 | 6 | |
| 20 | 11 |
About Shir‐Hwa Ueng
Shir‐Hwa Ueng is a scholar working on Pathology and Forensic Medicine, Cancer Research and Obstetrics and Gynecology, having authored 78 papers that have together received 1.8k indexed citations. Recurring topics across this work include Breast Cancer Treatment Studies (13 papers), Breast Lesions and Carcinomas (13 papers) and AI in cancer detection (10 papers). The work is most often cited by research in Obstetrics and Gynecology (239 citations), Cancer Research (408 citations) and Pathology and Forensic Medicine (424 citations). Shir‐Hwa Ueng has collaborated with scholars based in Taiwan, United States and United Kingdom. Frequent co-authors include Fattaneh A. Tavassoli, Yun‐Chung Cheung, Yung‐Feng Lo, Chuen Hsueh, Shin‐Cheh Chen, Hsiu-Pei Tsai, Kai‐Ping Chang, Sheng‐Po Hao, Yu‐Ching Lin and Wen‐Yu Chuang. Their work appears in journals such as Journal of Clinical Oncology, PLoS ONE and Clinical Cancer Research.
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.