Bo Liang

4.3k citations
23 papers · 2.7k indexed · 1 hit paper · h-index 12
Topics
COVID-19 Clinical Research Studies (11 papers)COVID-19 diagnosis using AI (8 papers)Radiomics and Machine Learning in Medical Imaging (5 papers)
Partner nations
ChinaUnited Kingdom

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...2020202620222024202050010001.5k

Peers

Bo Liang
Comparison fields: 5 of 127
  • Infectious Diseases 1.7k
  • Radiology, Nuclear Medicine and Imaging 1.2k
  • Neurology 757
  • Oncology 645
  • Pulmonary and Respiratory Medicine 473
Replace Tianhe Ye with:
Tianhe Ye China
Nanchuan Jiang China
Yanqing Fan China
Osamah Alwalid China
Heshui Shi China
Xingzhi Xie China
Xueyan Mei United States
Lian Yang China
Wenjian Xu China
Bo Liang relative to Tianhe Ye China Tianhe Ye's profile →
Citations per field
00.5×1.5×
Tianhe Ye · 1×
Citations per year

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
#WorkIndexed citations
1 0
2 12
3 3
4 6
5 72
6 18
7 1
8 17
9 33
10 4
11 3
12
Time Course of Lung Changes at Chest CT during Recovery from Coronavirus Disease 2019 (COVID-19)breakdown →
1928
13 154
14 56
15 289
16 94
17 1
18 18
19 17
20 4

About Bo Liang

Bo Liang is a scholar working on Infectious Diseases, Radiology, Nuclear Medicine and Imaging and Oncology, having authored 23 papers that have together received 2.7k indexed citations. Recurring topics across this 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). The work is most often cited by research in Infectious Diseases (1.7k citations), Critical Care and Intensive Care Medicine (373 citations) and Radiology, Nuclear Medicine and Imaging (1.2k citations). Bo Liang has collaborated with scholars based in China and United Kingdom. Frequent 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. Their work appears in journals such as Scientific Reports, Radiology and Frontiers in Immunology.

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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