Chung‐Ming Lo
Impact in
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- Radiomics and Machine Learning in Medical Imaging
- Ultrasound Imaging and Elastography
- MRI in cancer diagnosis
- COVID-19 diagnosis using AI
- Neurology top 5%
- Brain Tumor Detection and Classification
Papers in
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- Radiomics and Machine Learning in Medical Imaging 13
- Ultrasound Imaging and Elastography 7
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- AI in cancer detection 15
- Co-authors
- Ruey‐Feng Chang (23 shared papers)Kevin Li‐Chun Hsieh (7 shared papers)Chiun‐Sheng Huang (18 shared papers)Jeon‐Hor Chen (9 shared papers)Woo Kyung Moon (12 shared papers)Jung Min Chang (10 shared papers)Yeun‐Chung Chang (6 shared papers)Cheng‐Yu Chen (2 shared papers)
- Journals
- Computer Methods and Programs in Biomedicine (7 papers)Medical Physics (6 papers)Ultrasound in Medicine & Biology (6 papers)Applied Sciences (4 papers)PLoS ONE (4 papers)
- Partner nations
- TaiwanSouth KoreaUnited States
In The Last Decade
Chung‐Ming Lo
62 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 83
- Radiology, Nuclear Medicine and Imaging 588
- Neurology 208
- Health Informatics 24
- Artificial Intelligence 474
- Computer Vision and Pattern Recognition 251
Countries citing papers authored by Chung‐Ming Lo
This map shows the geographic impact of Chung‐Ming Lo'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 Chung‐Ming Lo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chung‐Ming Lo more than expected).
Fields of papers citing papers by Chung‐Ming Lo
This network shows the impact of papers produced by Chung‐Ming Lo. 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 Chung‐Ming Lo. The network helps show where Chung‐Ming Lo may publish in the future.
Co-authors
The 25 scholars most cited alongside Chung‐Ming Lo, 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 64 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 84 | |
| 2 | 2016 | 79 | |
| 3 | 2016 | 74 | |
| 4 | 2014 | 71 | |
| 5 | 2014 | 52 | |
| 6 | 2017 | 48 | |
| 7 | 2021 | 45 | |
| 8 | 2016 | 44 | |
| 9 | 2017 | 43 | |
| 10 | 2013 | 43 | |
| 11 | 2013 | 42 | |
| 12 | 2015 | 40 | |
| 13 | 2012 | 30 | |
| 14 | 2018 | 25 | |
| 15 | 2023 | 24 | |
| 16 | 2015 | 23 | |
| 17 | 2016 | 23 | |
| 18 | 2015 | 23 | |
| 19 | 2023 | 23 | |
| 20 | 1996 | 21 |
About Chung‐Ming Lo
Chung‐Ming Lo is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Pulmonary and Respiratory Medicine, Computer Vision and Pattern Recognition and Epidemiology, having authored 64 papers that have together received 1.3k indexed citations. Recurring topics across this work include AI in cancer detection (15 papers), Radiomics and Machine Learning in Medical Imaging (13 papers), Ultrasound Imaging and Elastography (7 papers), Breast Lesions and Carcinomas (5 papers), Image Retrieval and Classification Techniques (5 papers), Cerebrovascular and Carotid Artery Diseases (4 papers), Brain Tumor Detection and Classification (4 papers) and Colorectal Cancer Screening and Detection (4 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (588 citations), Neurology (208 citations), Health Informatics (24 citations), Artificial Intelligence (474 citations) and Computer Vision and Pattern Recognition (251 citations). Chung‐Ming Lo has collaborated with scholars based in Taiwan, South Korea and United States. Frequent co-authors include Ruey‐Feng Chang, Kevin Li‐Chun Hsieh, Chiun‐Sheng Huang, Jeon‐Hor Chen, Woo Kyung Moon, Jung Min Chang, Yeun‐Chung Chang, Cheng‐Yu Chen, Honghao Chen and Rong‐Tai Chen. Their work appears in journals such as Computer Methods and Programs in Biomedicine, Medical Physics, Ultrasound in Medicine & Biology, Applied Sciences 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.