Dawei Yang
Impact in
- Cancer Research top 5%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- Health Informatics top 5%
Papers in ⓘ
-
- Radiomics and Machine Learning in Medical Imaging 13
- COVID-19 diagnosis using AI 9
- Co-authors
- Chunxue Bai (28 shared papers)Charles A. Powell (8 shared papers)Yang Liu (1 shared paper)Xiandong Wang (1 shared paper)Yu Zhu (12 shared papers)Hongju Mao (8 shared papers)Jie Hu (8 shared papers)Yuanlin Song (7 shared papers)
- Journals
- Journal of Thoracic Oncology (6 papers)Biosensors and Bioelectronics (4 papers)Frontiers in Pharmacology (3 papers)Frontiers in Cell and Developmental Biology (2 papers)Nature Communications (2 papers)
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Dawei Yang
103 papers receiving 2.0k citations
Peers
Comparison fields: 5 of 162
- Cancer Research 447
- Health Informatics 31
- Pulmonary and Respiratory Medicine 490
- Radiology, Nuclear Medicine and Imaging 312
- Oncology 354
Countries citing papers authored by Dawei Yang
This map shows the geographic impact of Dawei Yang'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 Dawei Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dawei Yang more than expected).
Fields of papers citing papers by Dawei Yang
This network shows the impact of papers produced by Dawei Yang. 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 Dawei Yang. The network helps show where Dawei Yang may publish in the future.
Co-authors
The 25 scholars most cited alongside Dawei Yang, 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 112 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 227 | |
| 2 | 2020 | 104 | |
| 3 | 2022 | 87 | |
| 4 | 2018 | 80 | |
| 5 | 2014 | 79 | |
| 6 | 2020 | 77 | |
| 7 | 2023 | 71 | |
| 8 | 2017 | 69 | |
| 9 | 2021 | 68 | |
| 10 | 2016 | 60 | |
| 11 | 2022 | 58 | |
| 12 | 2021 | 56 | |
| 13 | 2021 | 43 | |
| 14 | 2012 | 43 | |
| 15 | 2020 | 40 | |
| 16 | 2018 | 38 | |
| 17 | 2019 | 34 | |
| 18 | 2017 | 34 | |
| 19 | 2015 | 34 | |
| 20 | 2016 | 33 |
About Dawei Yang
Dawei Yang is a scholar working on Otorhinolaryngology, Radiology, Nuclear Medicine and Imaging, Cancer Research, Oncology and Health Informatics, having authored 112 papers that have together received 2.0k indexed citations. Recurring topics across this work include Lung Cancer Diagnosis and Treatment (15 papers), Radiomics and Machine Learning in Medical Imaging (13 papers), COVID-19 diagnosis using AI (9 papers), Cancer-related molecular mechanisms research (7 papers), Lung Cancer Treatments and Mutations (7 papers), Lung Cancer Research Studies (6 papers), Viral-associated cancers and disorders (6 papers) and Quantum Dots Synthesis And Properties (6 papers). The work is most often cited by research in Cancer Research (447 citations), Health Informatics (31 citations), Pulmonary and Respiratory Medicine (490 citations), Radiology, Nuclear Medicine and Imaging (312 citations) and Oncology (354 citations). Dawei Yang has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Chunxue Bai, Charles A. Powell, Yang Liu, Xiandong Wang, Yu Zhu, Hongju Mao, Jie Hu, Yuanlin Song, Zhenhua Wu and Yuanlin Song. Their work appears in journals such as Journal of Thoracic Oncology, Biosensors and Bioelectronics, Frontiers in Pharmacology, Frontiers in Cell and Developmental Biology and Nature Communications.
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.