Ruijiang Li

8.5k total citations · 3 hit papers
153 papers, 5.3k citations indexed

About

Ruijiang Li is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Radiation. According to data from OpenAlex, Ruijiang Li has authored 153 papers receiving a total of 5.3k indexed citations (citations by other indexed papers that have themselves been cited), including 92 papers in Radiology, Nuclear Medicine and Imaging, 57 papers in Pulmonary and Respiratory Medicine and 47 papers in Radiation. Recurrent topics in Ruijiang Li's work include Medical Imaging Techniques and Applications (51 papers), Radiomics and Machine Learning in Medical Imaging (50 papers) and Advanced Radiotherapy Techniques (46 papers). Ruijiang Li is often cited by papers focused on Medical Imaging Techniques and Applications (51 papers), Radiomics and Machine Learning in Medical Imaging (50 papers) and Advanced Radiotherapy Techniques (46 papers). Ruijiang Li collaborates with scholars based in United States, China and Japan. Ruijiang Li's co-authors include Yi Cui, Jia Wu, Bailiang Li, Lei Xing, Maximilian Diehn, Steve Jiang, Issam El Naqa, Martin J. Murphy, John H. Lewis and Yuming Jiang and has published in prestigious journals such as Nature, Nature Communications and Journal of Clinical Oncology.

In The Last Decade

Ruijiang Li

145 papers receiving 5.2k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Development and Validation of an Individualized Immune Prognostic Signature in Early-Stage Nonsquamous Non–Small Cell Lung Cancer

2017 339 citations Bailiang Li, Yi Cui et al. profile →
Predicting peritoneal recurrence and disease-free survival from CT images in gastric cancer with multitask deep learning: a retrospective study

2022 102 citations Yuming Jiang, Qingyu Yuan et al. profile →
A vision–language foundation model for precision oncology

2025 48 citations Jinxi Xiang, Xiyue Wang et al. Nature profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Ruijiang Li United States	43	3.1k	1.7k	995	943	931	153	5.3k
Gary J. Whitman United States	40	2.4k 0.8×	1.1k 0.7×	194 0.2×	1.4k 1.5×	648 0.7×	266	6.2k
Johan van Soest Netherlands	22	4.2k 1.4×	1.7k 1.0×	447 0.4×	998 1.1×	1.1k 1.2×	79	5.3k
Binsheng Zhao United States	46	4.3k 1.4×	3.1k 1.8×	148 0.1×	1.3k 1.4×	1.3k 1.4×	140	6.5k
Marcus R. Makowski Germany	38	3.1k 1.0×	1.4k 0.8×	135 0.1×	445 0.5×	937 1.0×	362	6.7k
Xiaofeng Yang United States	45	5.0k 1.6×	1.7k 1.0×	2.2k 2.2×	276 0.3×	2.4k 2.6×	569	8.6k
Kenneth G. A. Gilhuijs Netherlands	37	2.8k 0.9×	779 0.5×	662 0.7×	605 0.6×	406 0.4×	117	4.4k
Carlos A. Perez United States	55	2.3k 0.7×	4.2k 2.5×	2.7k 2.7×	2.1k 2.2×	1.1k 1.2×	337	11.9k
Seán Walsh United States	24	3.9k 1.3×	1.6k 0.9×	152 0.2×	824 0.9×	1.0k 1.1×	56	5.5k
Patrick Großmann United States	17	6.8k 2.2×	3.1k 1.8×	163 0.2×	1.4k 1.5×	2.0k 2.1×	31	7.9k
Eric K. Oermann United States	32	1.1k 0.3×	1.1k 0.6×	225 0.2×	345 0.4×	580 0.6×	122	4.6k

Countries citing papers authored by Ruijiang Li

Since Specialization

Citations

This map shows the geographic impact of Ruijiang Li'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 Ruijiang Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ruijiang Li more than expected).

Fields of papers citing papers by Ruijiang Li

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ruijiang Li. 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 Ruijiang Li. The network helps show where Ruijiang Li may publish in the future.

Co-authorship network of co-authors of Ruijiang Li

This figure shows the co-authorship network connecting the top 25 collaborators of Ruijiang Li. A scholar is included among the top collaborators of Ruijiang Li 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 Ruijiang Li. Ruijiang Li is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Bai, Changsen, Lianlian Wu, Ruijiang Li, et al.. (2025). Machine Learning‐Enabled Drug‐Induced Toxicity Prediction. Advanced Science. 12(16). e2413405–e2413405. 14 indexed citations

Wang, Xiyue, Yuming Jiang, Sen Yang, et al.. (2025). Foundation Model for Predicting Prognosis and Adjuvant Therapy Benefit From Digital Pathology in GI Cancers. Journal of Clinical Oncology. 43(32). 3468–3481. 6 indexed citations

Li, Ruijiang, et al.. (2025). Regulatory Role of IGF2BP2 in Intestinal Mucosal Barrier Dysfunction in Ulcerative Colitis. The Turkish Journal of Gastroenterology. 36(5). 269–279. 1 indexed citations

Xiang, Jinxi, Xiyue Wang, Xiaoming Zhang, et al.. (2025). A vision–language foundation model for precision oncology. Nature. 638(8051). 769–778. 48 indexed citations breakdown →

Sun, Xiaoyu, et al.. (2025). The global research of magnetic resonance imaging in Alzheimer’s disease: a bibliometric analysis from 2004 to 2023. Frontiers in Neurology. 15. 1510522–1510522. 2 indexed citations

Jiang, Yuming, Kangneng Zhou, Zepang Sun, et al.. (2023). Non-invasive tumor microenvironment evaluation and treatment response prediction in gastric cancer using deep learning radiomics. Cell Reports Medicine. 4(8). 101146–101146. 62 indexed citations

Wang, Xi, Yuming Jiang, Hao Chen, et al.. (2023). Cancer immunotherapy response prediction from multi-modal clinical and image data using semi-supervised deep learning. Radiotherapy and Oncology. 186. 109793–109793. 12 indexed citations

Sali, Rasoul, et al.. (2023). Morphological diversity of cancer cells predicts prognosis across tumor types. JNCI Journal of the National Cancer Institute. 116(4). 555–564. 4 indexed citations

Jiang, Yuming, Bailiang Li, Zhen Han, et al.. (2023). Development and Validation of a Machine Learning Model for Detection and Classification of Tertiary Lymphoid Structures in Gastrointestinal Cancers. JAMA Network Open. 6(1). e2252553–e2252553. 40 indexed citations

10.

Chen, Weidao, Jiangfen Wu, Shuang Wu, et al.. (2022). Improving the diagnosis of acute ischemic stroke on non-contrast CT using deep learning: a multicenter study. Insights into Imaging. 13(1). 184–184. 23 indexed citations

11.

Wang, Haiyue, Yuming Jiang, Bailiang Li, et al.. (2020). Single-Cell Spatial Analysis of Tumor and Immune Microenvironment on Whole-Slide Image Reveals Hepatocellular Carcinoma Subtypes. Cancers. 12(12). 3562–3562. 26 indexed citations

12.

Fujima, Noriyuki, Akihiro Homma, Taisuke Harada, et al.. (2019). The utility of MRI histogram and texture analysis for the prediction of histological diagnosis in head and neck malignancies. Cancer Imaging. 19(1). 5–5. 56 indexed citations

13.

Li, Bailiang, Yi Cui, Dhanya K. Nambiar, John B. Sunwoo, & Ruijiang Li. (2019). The Immune Subtypes and Landscape of Squamous Cell Carcinoma. Clinical Cancer Research. 25(12). 3528–3537. 152 indexed citations

14.

Wu, Jia, Nasha Zhang, Fei Han, et al.. (2019). Integrating Tumor and Nodal Imaging Characteristics at Baseline and Mid-Treatment Computed Tomography Scans to Predict Distant Metastasis in Oropharyngeal Cancer Treated With Concurrent Chemoradiotherapy. International Journal of Radiation Oncology*Biology*Physics. 104(4). 942–952. 23 indexed citations

15.

Li, Bailiang, Yi Cui, Xiaoli Sun, et al.. (2018). A Quantitative CT Imaging Signature Predicts Survival and Complements Established Prognosticators in Stage I Non-Small Cell Lung Cancer. International Journal of Radiation Oncology*Biology*Physics. 102(4). 1098–1106. 20 indexed citations

16.

Cui, Yi, Bailiang Li, Erqi L. Pollom, Kathleen C. Horst, & Ruijiang Li. (2018). Integrating Radiosensitivity and Immune Gene Signatures for Predicting Benefit of Radiotherapy in Breast Cancer. Clinical Cancer Research. 24(19). 4754–4762. 51 indexed citations

17.

Wu, Jia, Yi Cui, Xiaoli Sun, et al.. (2017). Unsupervised Clustering of Quantitative Image Phenotypes Reveals Breast Cancer Subtypes with Distinct Prognoses and Molecular Pathways. Clinical Cancer Research. 23(13). 3334–3342. 77 indexed citations

18.

Li, Ruijiang, et al.. (2013). Automatic Prostate Tracking and Motion Assessment in Volumetric Modulated Arc Therapy With an Electronic Portal Imaging Device. International Journal of Radiation Oncology*Biology*Physics. 86(4). 762–768. 20 indexed citations

19.

Li, Bin, Xingquan Zhu, Ruijiang Li, et al.. (2011). Cross-domain collaborative filtering over time. International Joint Conference on Artificial Intelligence. 2293–2298. 44 indexed citations

20.

Jia, Xun, Yifei Lou, John H. Lewis, et al.. (2010). GPU-based Cone Beam CT Reconstruction via Total Variation Regularization. arXiv (Cornell University). 5 indexed citations

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.

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