Bo Liang

4.3k total citations · 1 hit paper
23 papers, 2.7k citations indexed

About

Bo Liang is a scholar working on Infectious Diseases, Radiology, Nuclear Medicine and Imaging and Oncology. According to data from OpenAlex, Bo Liang has authored 23 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Infectious Diseases, 12 papers in Radiology, Nuclear Medicine and Imaging and 7 papers in Oncology. Recurrent topics in Bo Liang's work include COVID-19 Clinical Research Studies (11 papers), COVID-19 diagnosis using AI (8 papers) and Radiomics and Machine Learning in Medical Imaging (5 papers). Bo Liang is often cited by papers focused on COVID-19 Clinical Research Studies (11 papers), COVID-19 diagnosis using AI (8 papers) and Radiomics and Machine Learning in Medical Imaging (5 papers). Bo Liang collaborates with scholars based in China and United Kingdom. Bo Liang's co-authors include Lian Yang, Feng Pan, Chuansheng Zheng, Lingli Li, Tianhe Ye, Jiazheng Wang, Dandan Zheng, Richard L. Hesketh, Peng Sun and Dehan Liu and has published in prestigious journals such as Scientific Reports, Radiology and Frontiers in Immunology.

In The Last Decade

Bo Liang

22 papers receiving 2.7k citations

Hit Papers

Time Course of Lung Changes at Chest CT during Recovery f... 2020 2026 2022 2024 2020 500 1000 1.5k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Bo Liang China 12 1.7k 1.2k 757 645 473 23 2.7k
Lian Yang China 19 1.7k 1.0× 1.3k 1.1× 842 1.1× 599 0.9× 513 1.1× 71 3.5k
Tianhe Ye China 11 1.4k 0.8× 1.2k 1.0× 659 0.9× 442 0.7× 425 0.9× 25 2.4k
Nanchuan Jiang China 7 1.8k 1.1× 1.0k 0.8× 920 1.2× 459 0.7× 469 1.0× 16 2.9k
Dandan Zheng China 6 1.3k 0.8× 1.1k 0.9× 571 0.8× 438 0.7× 368 0.8× 9 2.4k
Yanqing Fan China 10 2.2k 1.3× 1.2k 1.0× 1.2k 1.6× 563 0.9× 673 1.4× 16 3.4k
Osamah Alwalid China 13 2.0k 1.2× 1.2k 1.0× 1.2k 1.6× 518 0.8× 731 1.5× 36 3.4k
Heshui Shi China 10 1.8k 1.1× 1.5k 1.2× 783 1.0× 471 0.7× 497 1.1× 25 3.3k
Wenjian Xu China 10 1.1k 0.6× 1.4k 1.2× 394 0.5× 323 0.5× 380 0.8× 17 2.2k
Fang Zheng China 11 1.0k 0.6× 930 0.8× 473 0.6× 332 0.5× 205 0.4× 25 1.7k
Xueyan Mei United States 10 2.1k 1.2× 2.5k 2.1× 690 0.9× 608 0.9× 578 1.2× 29 4.0k

Countries citing papers authored by Bo Liang

Since Specialization
Citations

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

Fields of papers citing papers by Bo Liang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bo Liang

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

All Works

20 of 20 papers shown
2.
Guo, Yusheng, Yi Li, Jing Wang, et al.. (2024). Immune checkpoint inhibitors in cancer: the increased risk of atherosclerotic cardiovascular disease events and progression of coronary artery calcium. BMC Medicine. 22(1). 44–44. 12 indexed citations
3.
Li, Yi, Yusheng Guo, Lin Li, et al.. (2024). Bone mineral density as an individual prognostic biomarker in NSCLC patients treated with immune checkpoint inhibitors. Frontiers in Immunology. 15. 1332303–1332303. 3 indexed citations
4.
Cao, Yanyan, Lijie Zhang, Xiaopeng Guo, et al.. (2023). Effect of Probiotics and Fecal Microbiota Transplantation in Dirty Rats with Established Primary Liver Cancer. Future Microbiology. 19(2). 117–129. 5 indexed citations
5.
Lu, Xiaoting, Zhenhai Cui, Xiang Ma, et al.. (2022). The association of obesity with the progression and outcome of COVID‐19: The insight from an artificial‐intelligence‐based imaging quantitative analysis on computed tomography. Diabetes/Metabolism Research and Reviews. 38(4). e3519–e3519. 6 indexed citations
6.
Pan, Feng, Lian Yang, Bo Liang, et al.. (2021). Chest CT Patterns from Diagnosis to 1 Year of Follow-up in Patients with COVID-19. Radiology. 302(3). 709–719. 72 indexed citations
7.
Long, Xi, Lijie Zhang, Osamah Alwalid, et al.. (2021). Radiology department preventive and control measures and work plan during COVID-19 epidemic-experience from Wuhan. PubMed. 4(1). 1–8. 1 indexed citations
8.
Li, Lingli, Xuefeng Kan, Yongjun Zhao, et al.. (2021). Radiomics Signature: A potential biomarker for the prediction of survival in Advanced Hepatocellular Carcinoma. International Journal of Medical Sciences. 18(11). 2276–2284. 17 indexed citations
10.
Pan, Feng, Li Lin, Bo Liu, et al.. (2021). A novel deep learning-based quantification of serial chest computed tomography in Coronavirus Disease 2019 (COVID-19). Scientific Reports. 11(1). 417–417. 33 indexed citations
11.
Pan, Feng, Tianhe Ye, Peng Sun, et al.. (2020). Time Course of Lung Changes at Chest CT during Recovery from Coronavirus Disease 2019 (COVID-19). Radiology. 295(3). 715–721. 1928 indexed citations breakdown →
12.
Jiang, Nanchuan, Chuansheng Zheng, Yanqing Fan, et al.. (2020). CT appearances and short-term changes of COVID-19 in subclinical period. Zhonghua fangshexian yixue zazhi. 54(4). 305–309. 3 indexed citations
13.
Jiang, Nanchuan, Chuansheng Zheng, Yanqing Fan, et al.. (2020). CT appearance of new coronavirus pneumonia in subclinical period and short-term changes. Zhonghua fangshexian yixue zazhi. 54(12). 4 indexed citations
14.
Pan, Feng, Lian Yang, Yuncheng Li, et al.. (2020). Factors associated with death outcome in patients with severe coronavirus disease-19 (COVID-19): a case-control study. International Journal of Medical Sciences. 17(9). 1281–1292. 154 indexed citations
15.
He, Wenjuan, Lei Chen, Li Chen, et al.. (2020). COVID-19 in persons with haematological cancers. Leukemia. 34(6). 1637–1645. 289 indexed citations
16.
Li, Lingli, Lian Yang, Feng Pan, et al.. (2020). Association of clinical and radiographic findings with the outcomes of 93 patients with COVID-19 in Wuhan, China. Theranostics. 10(14). 6113–6121. 56 indexed citations
17.
Liu, Dehan, Feng Pan, Li Lin, et al.. (2020). The pulmonary sequalae in discharged patients with COVID-19: a short-term observational study. Respiratory Research. 21(1). 125–125. 94 indexed citations
18.
Cen, Dongzhi, Siwei Zhang, Zhiguang Chen, et al.. (2019). Renal cell carcinoma: predicting RUNX3 methylation level and its consequences on survival with CT features. European Radiology. 29(10). 5415–5422. 18 indexed citations
19.
Han, Ping, et al.. (2008). Multislice Spiral Computed Tomography Imaging in Congenital Inner Ear Malformations. Journal of Computer Assisted Tomography. 32(1). 146–150. 17 indexed citations
20.
Zeng, Fuqing, Heng Li, Zhewei Ye, et al.. (2007). Three-dimensional reconstruction on PC-Windows platform for evaluation of living donor nephrectomy. Computer Methods and Programs in Biomedicine. 86(1). 39–44. 4 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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