Yida Wang
Impact in
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- Radiomics and Machine Learning in Medical Imaging
- Advanced MRI Techniques and Applications
Papers in
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- Plant tissue culture and regeneration 3
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- Radiomics and Machine Learning in Medical Imaging 8
- MRI in cancer diagnosis 3
- Medical Imaging Techniques and Applications 3
- Co-authors
- Guang Yang (11 shared papers)Feng Huang (1 shared paper)Yuxin He (1 shared paper)Weichang Chen (1 shared paper)Yang Song (4 shared papers)Hang Qi (4 shared papers)Yong Wang (2 shared papers)Tianping Wang (3 shared papers)
- Journals
- Food Science and Human Wellness (2 papers)Journal of Magnetic Resonance Imaging (2 papers)European Journal of Radiology (2 papers)Journal of neurosurgery (2 papers)BMC Medical Education (1 paper)
- Partner nations
- ChinaUnited StatesJapan
In The Last Decade
Yida Wang
47 papers receiving 476 citations
Peers
Comparison fields: 5 of 97
- Health Informatics 7
- Radiology, Nuclear Medicine and Imaging 82
- Neurology 28
- Biological Psychiatry 8
- Neurology 40
Countries citing papers authored by Yida Wang
This map shows the geographic impact of Yida Wang'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 Yida Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yida Wang more than expected).
Fields of papers citing papers by Yida Wang
This network shows the impact of papers produced by Yida Wang. 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 Yida Wang. The network helps show where Yida Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Yida Wang, 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 49 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 68 | |
| 2 | 2021 | 40 | |
| 3 | 2019 | 26 | |
| 4 | 2022 | 25 | |
| 5 | 2021 | 24 | |
| 6 | 2023 | 21 | |
| 7 | 2023 | 21 | |
| 8 | 2024 | 20 | |
| 9 | 2023 | 19 | |
| 10 | 2023 | 17 | |
| 11 | 2007 | 17 | |
| 12 | 2022 | 14 | |
| 13 | 2017 | 13 | |
| 14 | 2021 | 12 | |
| 15 | 2022 | 10 | |
| 16 | 2018 | 9 | |
| 17 | 2020 | 8 | |
| 18 | 2023 | 8 | |
| 19 | 2021 | 7 | |
| 20 | 2022 | 7 |
About Yida Wang
Yida Wang is a scholar working on Molecular Biology, Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Surgery and Neurology, having authored 49 papers that have together received 483 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (8 papers), Endometrial and Cervical Cancer Treatments (3 papers), MRI in cancer diagnosis (3 papers), Plant tissue culture and regeneration (3 papers), Medical Imaging Techniques and Applications (3 papers), Cancer-related molecular mechanisms research (3 papers), Seaweed-derived Bioactive Compounds (3 papers) and Cerebrospinal fluid and hydrocephalus (2 papers). The work is most often cited by research in Health Informatics (7 citations), Radiology, Nuclear Medicine and Imaging (82 citations), Neurology (28 citations), Biological Psychiatry (8 citations) and Neurology (40 citations). Yida Wang has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Guang Yang, Feng Huang, Yuxin He, Weichang Chen, Yang Song, Hang Qi, Yong Wang, Tianping Wang, Xiancheng Chen and Nobuyuki Taniguchi. Their work appears in journals such as Food Science and Human Wellness, Journal of Magnetic Resonance Imaging, European Journal of Radiology, Journal of neurosurgery and BMC Medical Education.
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.