Dalong Wan
- Oncology top 10%
- Pancreatic and Hepatic Oncology Research 6
- Lung Cancer Research Studies 5
- Hepatology top 10%
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- Radiomics and Machine Learning in Medical Imaging 3
- Cancer Research top 10%
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- Gallbladder and Bile Duct Disorders 4
- Renal cell carcinoma treatment 3
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- Neuroendocrine Tumor Research Advances 8
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- Cholangiocarcinoma and Gallbladder Cancer Studies 3
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- Neuroblastoma Research and Treatments 2
- Co-authors
- Shusen ZhengJiacheng HuangShengzhang LinLin ZhouYiting QiaoLele ZhangWenjie LiangQiang Huang
- Partner nations
- ChinaGermanyMadagascar
In The Last Decade
Dalong Wan
27 papers receiving 1.1k citations
Hit Papers
Peers
Comparison fields: 5 of 89
- Oncology 439
- Hepatology 95
- Radiology, Nuclear Medicine and Imaging 256
- Cancer Research 162
- Pulmonary and Respiratory Medicine 240
Countries citing papers authored by Dalong Wan
This map shows the geographic impact of Dalong Wan'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 Dalong Wan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dalong Wan more than expected).
Fields of papers citing papers by Dalong Wan
This network shows the impact of papers produced by Dalong Wan. 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 Dalong Wan. The network helps show where Dalong Wan may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Dalong Wan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2024 | 2 | |
| 3 | 2023 | 4 | |
| 4 | 2022 | 1 | |
| 5 | Extracellular matrix and its therapeutic potential for cancer treatmentbreakdown → | 2021 | 580 |
| 6 | 2021 | 12 | |
| 7 | 2021 | 3 | |
| 8 | 2021 | 5 | |
| 9 | 2021 | 20 | |
| 10 | 2020 | 21 | |
| 11 | 2019 | 12 | |
| 12 | 2018 | 150 | |
| 13 | 2018 | 10 | |
| 14 | 2018 | 91 | |
| 15 | 2018 | 14 | |
| 16 | 2018 | 32 | |
| 17 | 2017 | 2 | |
| 18 | 2016 | 1 | |
| 19 | 2016 | 6 | |
| 20 | 2016 | 7 |
About Dalong Wan
Dalong Wan is a scholar working on Oncology, Gastroenterology, Pulmonary and Respiratory Medicine, Epidemiology and Neurology, having authored 30 papers that have together received 1.1k indexed citations. Recurring topics across this work include Neuroendocrine Tumor Research Advances (8 papers), Pancreatic and Hepatic Oncology Research (6 papers), Lung Cancer Research Studies (5 papers), Gallbladder and Bile Duct Disorders (4 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), Renal cell carcinoma treatment (3 papers), Cholangiocarcinoma and Gallbladder Cancer Studies (3 papers) and Neuroblastoma Research and Treatments (2 papers). The work is most often cited by research in Oncology (439 citations), Hepatology (95 citations), Radiology, Nuclear Medicine and Imaging (256 citations), Cancer Research (162 citations) and Pulmonary and Respiratory Medicine (240 citations). Dalong Wan has collaborated with scholars based in China, Germany and Madagascar. Frequent co-authors include Shusen Zheng, Jiacheng Huang, Shengzhang Lin, Lin Zhou, Yiting Qiao, Lele Zhang, Wenjie Liang, Lele Zhang, Qiang Huang and Tianye Niu. Their work appears in journals such as Medicine, Frontiers in Oncology, Frontiers in Medicine, World Journal of Surgical Oncology and Clinical Cancer Research.
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.