Mingchen Gao
Impact in
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- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
- Health Informatics top 1%
Papers in
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- Medical Image Segmentation Techniques 15
- Multimodal Machine Learning Applications 6
- Advanced Neural Network Applications 6
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- Radiomics and Machine Learning in Medical Imaging 12
- COVID-19 diagnosis using AI 9
- Medical Imaging Techniques and Applications 7
- Co-authors
- Ziyue Xu (12 shared papers)Daniel J. Mollura (12 shared papers)Le Lu (6 shared papers)Ronald M. Summers (5 shared papers)Hoo-Chang Shin (3 shared papers)Holger R. Roth (3 shared papers)Isabella Nogues (3 shared papers)Jianhua Yao (2 shared papers)
- Journals
- Lecture notes in computer science (20 papers)Advances in computer vision and pattern recognition (2 papers)IEEE Transactions on Medical Imaging (2 papers)Medical Image Analysis (2 papers)Chemical Engineering Journal (2 papers)
- Partner nations
- United StatesChinaUnited Kingdom
In The Last Decade
Mingchen Gao
65 papers receiving 5.8k citations
Mingchen Gao's Hit Papers
Peers
Comparison fields: 5 of 184
- Radiology, Nuclear Medicine and Imaging 2.0k
- Health Informatics 127
- Computer Vision and Pattern Recognition 1.8k
- Artificial Intelligence 2.2k
- Neurology 479
Countries citing papers authored by Mingchen Gao
This map shows the geographic impact of Mingchen Gao'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 Mingchen Gao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mingchen Gao more than expected).
Fields of papers citing papers by Mingchen Gao
This network shows the impact of papers produced by Mingchen Gao. 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 Mingchen Gao. The network helps show where Mingchen Gao may publish in the future.
Co-authors
The 25 scholars most cited alongside Mingchen Gao, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 73 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning Hit paper breakdown → | 2016 | 4548 |
| 2 | 2016 | 209 | |
| 3 | 2011 | 206 | |
| 4 | 2019 | 83 | |
| 5 | 2021 | 79 | |
| 6 | 2016 | 66 | |
| 7 | 2019 | 59 | |
| 8 | 2019 | 45 | |
| 9 | 2016 | 41 | |
| 10 | 1991 | 40 | |
| 11 | 2021 | 36 | |
| 12 | 2016 | 35 | |
| 13 | 2019 | 34 | |
| 14 | 2018 | 33 | |
| 15 | 2021 | 31 | |
| 16 | 2018 | 29 | |
| 17 | 2012 | 27 | |
| 18 | 2021 | 27 | |
| 19 | 2011 | 25 | |
| 20 | 2022 | 24 |
About Mingchen Gao
Mingchen Gao is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Neurology and Pulmonary and Respiratory Medicine, having authored 73 papers that have together received 6.0k indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (15 papers), Radiomics and Machine Learning in Medical Imaging (12 papers), COVID-19 diagnosis using AI (9 papers), Lung Cancer Diagnosis and Treatment (8 papers), Domain Adaptation and Few-Shot Learning (7 papers), Medical Imaging Techniques and Applications (7 papers), Multimodal Machine Learning Applications (6 papers) and Advanced Neural Network Applications (6 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (2.0k citations), Health Informatics (127 citations), Computer Vision and Pattern Recognition (1.8k citations), Artificial Intelligence (2.2k citations) and Neurology (479 citations). Mingchen Gao has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Ziyue Xu, Daniel J. Mollura, Le Lu, Ronald M. Summers, Hoo-Chang Shin, Holger R. Roth, Isabella Nogues, Jianhua Yao, Dimitris Metaxas and Yan Shen. Their work appears in journals such as Lecture notes in computer science, Advances in computer vision and pattern recognition, IEEE Transactions on Medical Imaging, Medical Image Analysis and Chemical Engineering Journal.
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.