Qian Da
Impact in
- Ocean Engineering top 5%
- Enhanced Oil Recovery Techniques
- Drilling and Well Engineering
Papers in
-
- Enhanced Oil Recovery Techniques 7
-
- Radiomics and Machine Learning in Medical Imaging 5
- Co-authors
- Guanglun Lei (6 shared papers)Chuanjin Yao (6 shared papers)Yuliang Su (3 shared papers)Lei Li (2 shared papers)Xue Zhang (2 shared papers)Liyi Ma (1 shared paper)Qiang Zhou (1 shared paper)Guozhong Zhang (1 shared paper)
- Journals
- Artificial Intelligence in Medicine (1 paper)Scientific Reports (1 paper)The American Journal of Surgical Pathology (1 paper)Applied Energy (1 paper)BMC Neurology (1 paper)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Qian Da
22 papers receiving 310 citations
Peers
Comparison fields: 5 of 78
- Ocean Engineering 129
- Health Informatics 6
- Mechanics of Materials 86
- Analytical Chemistry 31
- Environmental Engineering 32
Countries citing papers authored by Qian Da
This map shows the geographic impact of Qian Da'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 Qian Da with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qian Da more than expected).
Fields of papers citing papers by Qian Da
This network shows the impact of papers produced by Qian Da. 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 Qian Da. The network helps show where Qian Da may publish in the future.
Co-authors
The 25 scholars most cited alongside Qian Da, 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 24 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 72 | |
| 2 | 2022 | 39 | |
| 3 | 2017 | 31 | |
| 4 | 2023 | 30 | |
| 5 | 2023 | 27 | |
| 6 | 2022 | 21 | |
| 7 | 2022 | 17 | |
| 8 | 2021 | 11 | |
| 9 | 2022 | 11 | |
| 10 | 2022 | 11 | |
| 11 | 2022 | 8 | |
| 12 | 2024 | 7 | |
| 13 | 2024 | 5 | |
| 14 | 2022 | 4 | |
| 15 | 2020 | 4 | |
| 16 | 2022 | 4 | |
| 17 | 2024 | 3 | |
| 18 | 2018 | 3 | |
| 19 | 2018 | 3 | |
| 20 | Urban traffic sharing information service platform with data warehouse technique | 2002 | 1 |
About Qian Da
Qian Da is a scholar working on Ocean Engineering, Radiology, Nuclear Medicine and Imaging, Pathology and Forensic Medicine, Mechanics of Materials and Artificial Intelligence, having authored 24 papers that have together received 314 indexed citations. Recurring topics across this work include Enhanced Oil Recovery Techniques (7 papers), Radiomics and Machine Learning in Medical Imaging (5 papers), Hydrocarbon exploration and reservoir analysis (4 papers), AI in cancer detection (4 papers), Lymphoma Diagnosis and Treatment (3 papers), Hydraulic Fracturing and Reservoir Analysis (3 papers), CO2 Sequestration and Geologic Interactions (2 papers) and Microbial bioremediation and biosurfactants (2 papers). The work is most often cited by research in Ocean Engineering (129 citations), Health Informatics (6 citations), Mechanics of Materials (86 citations), Analytical Chemistry (31 citations) and Environmental Engineering (32 citations). Qian Da has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Guanglun Lei, Chuanjin Yao, Yuliang Su, Lei Li, Xue Zhang, Xue Zhang, Liyi Ma, Qiang Zhou, Guozhong Zhang and Zhihui Wang. Their work appears in journals such as Artificial Intelligence in Medicine, Scientific Reports, The American Journal of Surgical Pathology, Applied Energy and BMC Neurology.
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.