Maode Lai
Impact in
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- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
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- Digital Imaging for Blood Diseases
- Image Retrieval and Classification Techniques
- Advanced Neural Network Applications
Papers in
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- AI in cancer detection 18
- Oncology 19
- Colorectal Cancer Screening and Detection 9
- Co-authors
- Yan Xu (20 shared papers)Eric Chang (14 shared papers)Enping Xu (10 shared papers)Qiong Huang (14 shared papers)Yuqing Ai (2 shared papers)Zhipeng Jia (2 shared papers)Yubo Fan (10 shared papers)Bingjian Lü (7 shared papers)
- Journals
- IEEE Transactions on Medical Imaging (3 papers)Molecular Cancer (2 papers)Carcinogenesis (2 papers)Oncotarget (2 papers)Scientific Reports (2 papers)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Maode Lai
71 papers receiving 3.1k citations
Maode Lai's Hit Papers
Peers
Comparison fields: 5 of 146
- Radiology, Nuclear Medicine and Imaging 705
- Computer Vision and Pattern Recognition 740
- Artificial Intelligence 1.1k
- Biophysics 166
- Oncology 619
Countries citing papers authored by Maode Lai
This map shows the geographic impact of Maode Lai'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 Maode Lai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maode Lai more than expected).
Fields of papers citing papers by Maode Lai
This network shows the impact of papers produced by Maode Lai. 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 Maode Lai. The network helps show where Maode Lai may publish in the future.
Co-authors
The 25 scholars most cited alongside Maode Lai, 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 71 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Large scale tissue histopathology image classification, segmentation, and visualization via deep convolutional activation features Hit paper breakdown → | 2017 | 320 |
| 2 | 2014 | 264 | |
| 3 | 2018 | 232 | |
| 4 | 2014 | 228 | |
| 5 | 2009 | 155 | |
| 6 | 2015 | 140 | |
| 7 | 2017 | 136 | |
| 8 | 2015 | 132 | |
| 9 | 2020 | 117 | |
| 10 | 2008 | 113 | |
| 11 | 2016 | 81 | |
| 12 | 2018 | 80 | |
| 13 | 2017 | 79 | |
| 14 | 2007 | 78 | |
| 15 | 2016 | 74 | |
| 16 | 2009 | 72 | |
| 17 | 2009 | 57 | |
| 18 | 2003 | 50 | |
| 19 | 2015 | 45 | |
| 20 | 2006 | 44 |
About Maode Lai
Maode Lai is a scholar working on Artificial Intelligence, Oncology, Computer Vision and Pattern Recognition, Molecular Biology and Pathology and Forensic Medicine, having authored 71 papers that have together received 3.2k indexed citations. Recurring topics across this work include AI in cancer detection (18 papers), Digital Imaging for Blood Diseases (9 papers), Colorectal Cancer Screening and Detection (9 papers), Growth Hormone and Insulin-like Growth Factors (8 papers), Genetic factors in colorectal cancer (8 papers), Radiomics and Machine Learning in Medical Imaging (7 papers), Image Retrieval and Classification Techniques (7 papers) and Metabolism, Diabetes, and Cancer (4 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (705 citations), Computer Vision and Pattern Recognition (740 citations), Artificial Intelligence (1.1k citations), Biophysics (166 citations) and Oncology (619 citations). Maode Lai has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Yan Xu, Eric Chang, Enping Xu, Qiong Huang, Yuqing Ai, Zhipeng Jia, Yubo Fan, Bingjian Lü, Zhuowen Tu and Fangying Xu. Their work appears in journals such as IEEE Transactions on Medical Imaging, Molecular Cancer, Carcinogenesis, Oncotarget and Scientific Reports.
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.