Benjamin Q. Huynh

1.6k total citations · 2 hit papers
20 papers, 1.1k citations indexed

About

Benjamin Q. Huynh is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Health, Toxicology and Mutagenesis. According to data from OpenAlex, Benjamin Q. Huynh has authored 20 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Radiology, Nuclear Medicine and Imaging, 8 papers in Artificial Intelligence and 4 papers in Health, Toxicology and Mutagenesis. Recurrent topics in Benjamin Q. Huynh's work include Radiomics and Machine Learning in Medical Imaging (10 papers), AI in cancer detection (8 papers) and MRI in cancer diagnosis (6 papers). Benjamin Q. Huynh is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (10 papers), AI in cancer detection (8 papers) and MRI in cancer diagnosis (6 papers). Benjamin Q. Huynh collaborates with scholars based in United States, United Kingdom and Germany. Benjamin Q. Huynh's co-authors include Maryellen L. Giger, Hui Li, Elizabeth T. Chin, Sanjay Basu, Karen Drukker, Nathan C. Lo, Н. В. Антропова, Lloyd A. C. Chapman, Mathew V. Kiang and Matthew Murrill and has published in prestigious journals such as Clinical Infectious Diseases, The Lancet Infectious Diseases and Medical Physics.

In The Last Decade

Benjamin Q. Huynh

18 papers receiving 1.1k citations

Hit Papers

Digital mammographic tumo... 2016 2026 2019 2022 2016 2017 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Digital mammographic tumor classification using transfer learning from deep convolutional neural networks
    2016 393 citations Benjamin Q. Huynh, Hui Li et al. Journal of Medical Imaging profile →
  2. A deep feature fusion methodology for breast cancer diagnosis demonstrated on three imaging modality datasets
    2017 298 citations Benjamin Q. Huynh, Maryellen L. Giger et al. Medical Physics profile →

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Benjamin Q. Huynh 717 648 155 142 116 20 1.1k
Ali Abbasian Ardakani 996 1.4× 536 0.8× 160 1.0× 126 0.9× 210 1.8× 53 1.4k
Carson Lam 606 0.8× 275 0.4× 106 0.7× 179 1.3× 55 0.5× 25 1.1k
Dijia Wu 752 1.0× 354 0.5× 162 1.0× 129 0.9× 115 1.0× 28 1.0k
Yunfei Zha 1.4k 1.9× 653 1.0× 270 1.7× 152 1.1× 167 1.4× 74 1.9k
Ying Song 951 1.3× 397 0.6× 188 1.2× 136 1.0× 243 2.1× 56 1.5k
Anuj Pareek 634 0.9× 639 1.0× 161 1.0× 111 0.8× 159 1.4× 23 1.5k
Cathal McCague 467 0.7× 269 0.4× 82 0.5× 41 0.3× 98 0.8× 11 737
Mohamed Amgad 717 1.0× 692 1.1× 156 1.0× 195 1.4× 72 0.6× 32 1.6k
Yuchen Qiu 1.1k 1.5× 859 1.3× 271 1.7× 331 2.3× 238 2.1× 62 1.8k

Countries citing papers authored by Benjamin Q. Huynh

Since Specialization
Citations

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

Fields of papers citing papers by Benjamin Q. Huynh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Benjamin Q. Huynh. 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 Benjamin Q. Huynh. The network helps show where Benjamin Q. Huynh may publish in the future.

Co-authorship network of co-authors of Benjamin Q. Huynh

This figure shows the co-authorship network connecting the top 25 collaborators of Benjamin Q. Huynh. A scholar is included among the top collaborators of Benjamin Q. Huynh 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 Benjamin Q. Huynh. Benjamin Q. Huynh is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Huynh, Benjamin Q., Elizabeth T. Chin, & Mathew V. Kiang. (2024). Estimated Childhood Lead Exposure From Drinking Water in Chicago. JAMA Pediatrics. 178(5). 473–473. 6 indexed citations
2.
Huynh, Benjamin Q., Elizabeth T. Chin, Allison Koenecke, et al.. (2024). Mitigating allocative tradeoffs and harms in an environmental justice data tool. Nature Machine Intelligence. 6(2). 187–194. 4 indexed citations
3.
Huynh, Benjamin Q. & Mathew V. Kiang. (2024). AI for Anticipatory Action: Moving beyond Climate Forecasting. Proceedings of the AAAI Symposium Series. 2(1). 78–84.
4.
Huynh, Benjamin Q., et al.. (2024). Aspartame exposures in the US population: Demonstration of a novel approach for exposure estimates to food additives using NHANES data. Journal of Exposure Science & Environmental Epidemiology. 35(3). 351–361. 3 indexed citations
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Huynh, Benjamin Q., Laura H. Kwong, Mathew V. Kiang, et al.. (2021). Public health impacts of an imminent Red Sea oil spill. Nature Sustainability. 4(12). 1084–1091. 50 indexed citations
8.
Kiang, Mathew V., Elizabeth T. Chin, Benjamin Q. Huynh, et al.. (2021). Routine asymptomatic testing strategies for airline travel during the COVID-19 pandemic: a simulation study. The Lancet Infectious Diseases. 21(7). 929–938. 42 indexed citations
9.
Chin, Elizabeth T., Benjamin Q. Huynh, Lloyd A. C. Chapman, et al.. (2020). Frequency of Routine Testing for Coronavirus Disease 2019 (COVID-19) in High-risk Healthcare Environments to Reduce Outbreaks. Clinical Infectious Diseases. 73(9). e3127–e3129. 61 indexed citations
10.
Chin, Elizabeth T., Benjamin Q. Huynh, Nathan C. Lo, Trevor Hastie, & Sanjay Basu. (2020). Projected geographic disparities in healthcare worker absenteeism from COVID-19 school closures and the economic feasibility of child care subsidies: a simulation study. BMC Medicine. 18(1). 218–218. 19 indexed citations
11.
Huynh, Benjamin Q., et al.. (2018). Breast lesion classification based on dynamic contrast-enhanced magnetic resonance images sequences with long short-term memory networks. Journal of Medical Imaging. 6(1). 1–1. 28 indexed citations
12.
Huynh, Benjamin Q., Н. В. Антропова, & Maryellen L. Giger. (2018). Recurrent neural networks for breast lesion classification based on DCE-MRIs. 16. 93–93. 8 indexed citations
13.
Huynh, Benjamin Q., Н. В. Антропова, & Maryellen L. Giger. (2017). Comparison of breast DCE-MRI contrast time points for predicting response to neoadjuvant chemotherapy using deep convolutional neural network features with transfer learning. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 10134. 101340U–101340U. 27 indexed citations
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Drukker, Karen, Benjamin Q. Huynh, Maryellen L. Giger, et al.. (2017). Deep learning and three-compartment breast imaging in breast cancer diagnosis. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 10134. 101341F–101341F. 3 indexed citations
16.
Huynh, Benjamin Q., et al.. (2017). A deep feature fusion methodology for breast cancer diagnosis demonstrated on three imaging modality datasets. Medical Physics. 44(10). 5162–5171. 298 indexed citations breakdown →
17.
Антропова, Н. В., Benjamin Q. Huynh, & Maryellen L. Giger. (2017). Performance comparison of deep learning and segmentation-based radiomic methods in the task of distinguishing benign and malignant breast lesions on DCE-MRI. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 10134. 101341G–101341G. 11 indexed citations
18.
Huynh, Benjamin Q., Hui Li, & Maryellen L. Giger. (2016). Digital mammographic tumor classification using transfer learning from deep convolutional neural networks. Journal of Medical Imaging. 3(3). 34501–34501. 393 indexed citations breakdown →
19.
Huynh, Benjamin Q., et al.. (2016). SU‐D‐207B‐06: Predicting Breast Cancer Malignancy On DCE‐MRI Data Using Pre‐Trained Convolutional Neural Networks. Medical Physics. 43(6Part4). 3349–3350. 23 indexed citations
20.
Huynh, Benjamin Q., Karen Drukker, & Maryellen L. Giger. (2016). MO-DE-207B-06: Computer-Aided Diagnosis of Breast Ultrasound Images Using Transfer Learning From Deep Convolutional Neural Networks. Medical Physics. 43(6Part30). 3705–3705. 64 indexed citations

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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