Ri-Qiang Liao
- Oncology top 5%
- Pulmonary and Respiratory Medicine top 2%
- Molecular Biology
- Cancer Research top 10%
- Immunology top 10%
- Co-authors
- Yi‐Long WuWen‐Zhao ZhongXue‐Ning YangXu‐Chao ZhangJin‐Ji YangJian SuSi-Pei WuZhong‐Yi Dong
- Topics
- Lung Cancer Diagnosis and Treatment (24 papers)Lung Cancer Treatments and Mutations (22 papers)Radiomics and Machine Learning in Medical Imaging (10 papers)
- Journals
- Journal of Clinical OncologySHILAP Revista de lepidopterologíaClinical Cancer Research
- Partner nations
- China
In The Last Decade
Ri-Qiang Liao
35 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 77
- Oncology 917
- Pulmonary and Respiratory Medicine 905
- Molecular Biology 314
- Cancer Research 286
- Immunology 233
Countries citing papers authored by Ri-Qiang Liao
This map shows the geographic impact of Ri-Qiang Liao'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 Ri-Qiang Liao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ri-Qiang Liao more than expected).
Fields of papers citing papers by Ri-Qiang Liao
This network shows the impact of papers produced by Ri-Qiang Liao. 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 Ri-Qiang Liao. The network helps show where Ri-Qiang Liao may publish in the future.
Co-authorship network of co-authors of Ri-Qiang Liao
This figure shows the co-authorship network connecting the top 25 collaborators of Ri-Qiang Liao. A scholar is included among the top collaborators of Ri-Qiang Liao based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ri-Qiang Liao. Ri-Qiang Liao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 6 | |
| 2 | 1 | |
| 3 | 2 | |
| 4 | 9 | |
| 5 | 17 | |
| 6 | 16 | |
| 7 | 1 | |
| 8 | 1 | |
| 9 | 2 | |
| 10 | 120 | |
| 11 | 1 | |
| 12 | 4 | |
| 13 | Potential Predictive Value of TP53 and KRAS Mutation Status for Response to PD-1 Blockade Immunotherapy in Lung Adenocarcinomabreakdown → | 741 |
| 14 | 22 | |
| 15 | 75 | |
| 16 | 8 | |
| 17 | 14 | |
| 18 | 10 | |
| 19 | 141 | |
| 20 | 23 |
About Ri-Qiang Liao
Ri-Qiang Liao is a scholar working on Pulmonary and Respiratory Medicine, Oncology and Radiology, Nuclear Medicine and Imaging, having authored 36 papers that have together received 1.4k indexed citations. Recurring topics across this work include Lung Cancer Diagnosis and Treatment (24 papers), Lung Cancer Treatments and Mutations (22 papers) and Radiomics and Machine Learning in Medical Imaging (10 papers). The work is most often cited by research in Oncology (917 citations), Pulmonary and Respiratory Medicine (905 citations) and Cancer Research (286 citations). Ri-Qiang Liao has collaborated with scholars based in China. Frequent co-authors include Yi‐Long Wu, Wen‐Zhao Zhong, Xue‐Ning Yang, Xu‐Chao Zhang, Jin‐Ji Yang, Jian Su, Si-Pei Wu, Zhong‐Yi Dong, Qing Zhou and Hong‐Hong Yan. Their work appears in journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología 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.