Erich P. Huang
- Radiology, Nuclear Medicine and Imaging top 0.5%
- Pulmonary and Respiratory Medicine top 2%
- Oncology top 5%
- Cancer Research top 5%
- Surgery top 10%
- Co-authors
- Lalitha ShankarLawrence H. SchwartzElisabeth G.E. de VriesAlice P. ChenPatrick TherasseJan BogaertsSumithra J. MandrekarNancy U. Lin
- Topics
- Radiomics and Machine Learning in Medical Imaging (22 papers)Statistical Methods in Clinical Trials (11 papers)Cancer Genomics and Diagnostics (8 papers)
- Partner nations
- United StatesUnited KingdomNetherlands
In The Last Decade
Erich P. Huang
36 papers receiving 3.1k citations
Hit Papers
Peers
Comparison fields: 5 of 109
- Radiology, Nuclear Medicine and Imaging 1.7k
- Pulmonary and Respiratory Medicine 978
- Oncology 974
- Cancer Research 457
- Surgery 400
Countries citing papers authored by Erich P. Huang
This map shows the geographic impact of Erich P. Huang'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 Erich P. Huang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Erich P. Huang more than expected).
Fields of papers citing papers by Erich P. Huang
This network shows the impact of papers produced by Erich P. Huang. 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 Erich P. Huang. The network helps show where Erich P. Huang may publish in the future.
Co-authorship network of co-authors of Erich P. Huang
This figure shows the co-authorship network connecting the top 25 collaborators of Erich P. Huang. A scholar is included among the top collaborators of Erich P. Huang 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 Erich P. Huang. Erich P. Huang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 2 | |
| 3 | 6 | |
| 4 | Criteria for the translation of radiomics into clinically useful testsbreakdown → | 127 |
| 5 | 3 | |
| 6 | 6 | |
| 7 | 30 | |
| 8 | 6 | |
| 9 | 6 | |
| 10 | 10 | |
| 11 | 3 | |
| 12 | 29 | |
| 13 | 6 | |
| 14 | 27 | |
| 15 | 4 | |
| 16 | RECIST 1.1—Update and clarification: From the RECIST committeebreakdown → | 1206 |
| 17 | MR Imaging Radiomics Signatures for Predicting the Risk of Breast Cancer Recurrence as Given by Research Versions of MammaPrint, Oncotype DX, and PAM50 Gene Assaysbreakdown → | 373 |
| 18 | 221 | |
| 19 | Quantitative MRI radiomics in the prediction of molecular classifications of breast cancer subtypes in the TCGA/TCIA data setbreakdown → | 287 |
| 20 | 90 |
About Erich P. Huang
Erich P. Huang is a scholar working on Statistics and Probability, Radiology, Nuclear Medicine and Imaging and Health Informatics, having authored 38 papers that have together received 3.1k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (22 papers), Statistical Methods in Clinical Trials (11 papers) and Cancer Genomics and Diagnostics (8 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (1.7k citations), Health Informatics (77 citations) and Oncology (974 citations). Erich P. Huang has collaborated with scholars based in United States, United Kingdom and Netherlands. Frequent co-authors include Lalitha Shankar, Lawrence H. Schwartz, Elisabeth G.E. de Vries, Alice P. Chen, Patrick Therasse, Jan Bogaerts, Sumithra J. Mandrekar, Nancy U. Lin, Lesley Seymour and Stephen J. Gwyther. Their work appears in journals such as The Lancet, Journal of Clinical Oncology and Blood.
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.