Leibo Liu

1.3k total citations
8 papers, 46 citations indexed

About

Leibo Liu is a scholar working on Artificial Intelligence, Molecular Biology and Epidemiology. According to data from OpenAlex, Leibo Liu has authored 8 papers receiving a total of 46 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 4 papers in Molecular Biology and 2 papers in Epidemiology. Recurrent topics in Leibo Liu's work include Machine Learning in Healthcare (6 papers), Topic Modeling (6 papers) and Biomedical Text Mining and Ontologies (4 papers). Leibo Liu is often cited by papers focused on Machine Learning in Healthcare (6 papers), Topic Modeling (6 papers) and Biomedical Text Mining and Ontologies (4 papers). Leibo Liu collaborates with scholars based in Australia, United Kingdom and China. Leibo Liu's co-authors include Anthony Nguyen, Vicki Bennett, Oscar Perez‐Concha, Louisa Jorm, Geoff P. Delaney, Craig S. Anderson, Qiang Li, Xiaoqiu Liu, Xinwen Ren and Shoujiang You and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of the American Medical Informatics Association and Journal of Biomedical Informatics.

In The Last Decade

Leibo Liu

4 papers receiving 45 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Leibo Liu Australia	4	41	22	14	3	3	8	46
Vidul Ayakulangara Panickan United States	5	20 0.5×	12 0.5×	10 0.7×	3 1.0×	3 1.0×	8	39
Niall Taylor United Kingdom	4	24 0.6×	7 0.3×	5 0.4×		4 1.3×	5	32
Chimezie Ogbuji United States	4	23 0.6×	17 0.8×	10 0.7×			5	32
Frieda Steurs Belgium	4	21 0.5×	7 0.3×	2 0.1×			14	31
Zelalem Gero United States	4	25 0.6×	12 0.5×	1 0.1×		3 1.0×	9	39
SV Ramanan India	4	22 0.5×	22 1.0×	1 0.1×	1 0.3×		6	26
Y. C. Zhu China	2	21 0.5×	3 0.1×	3 0.2×		4 1.3×	5	36
Jignesh Bhate Germany	3	13 0.3×	19 0.9×	1 0.1×			5	34
Hagar Hussein Egypt	4	14 0.3×	7 0.3×			2 0.7×	6	34
Greg Strylewicz United States	3	6 0.1×	4 0.2×	4 0.3×		2 0.7×	3	28

Countries citing papers authored by Leibo Liu

Since Specialization

Citations

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

Fields of papers citing papers by Leibo Liu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Leibo Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Leibo Liu. A scholar is included among the top collaborators of Leibo Liu 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 Leibo Liu. Leibo Liu 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:

8 of 8 papers shown

1.

Zhou, Zien, Sohei Yoshimura, Yuki Sakamoto, et al.. (2025). Intravenous thrombolysis in patients with acute ischemic stroke and cerebral microbleeds: Results from the ENCHANTED trial. International Journal of Stroke. 1109124847–1109124847.

2.

Ren, Xinwen, Chen Chen, Menglu Ouyang, et al.. (2025). Early blood pressure lowering and cerebral oedema in thrombolysis-treated stroke: secondary analysis of the ENCHANTED trial. Stroke and Vascular Neurology. svn–2025.

3.

Liu, Leibo, Victoria Blake, Tim Churches, et al.. (2025). Using natural language processing to extract information from clinical text in electronic medical records for populating clinical registries: a systematic review. Journal of the American Medical Informatics Association. 33(2). 484–499.

4.

Liu, Leibo, et al.. (2024). Adapting Large Language Models for Automated Summarisation of Electronic Medical Records in Clinical Coding. Studies in health technology and informatics. 318. 24–29.

5.

Liu, Leibo, Oscar Perez‐Concha, Anthony Nguyen, et al.. (2023). Web-Based Application Based on Human-in-the-Loop Deep Learning for Deidentifying Free-Text Data in Electronic Medical Records: Development and Usability Study. SHILAP Revista de lepidopterología. 12. e46322–e46322. 3 indexed citations

6.

Liu, Leibo, Oscar Perez‐Concha, Anthony Nguyen, Vicki Bennett, & Louisa Jorm. (2023). Automated ICD coding using extreme multi-label long text transformer-based models. Artificial Intelligence in Medicine. 144. 102662–102662. 14 indexed citations

7.

Liu, Leibo, Oscar Perez‐Concha, Anthony Nguyen, Vicki Bennett, & Louisa Jorm. (2022). De-identifying Australian hospital discharge summaries: An end-to-end framework using ensemble of deep learning models. Journal of Biomedical Informatics. 135. 104215–104215. 9 indexed citations

8.

Liu, Leibo, Oscar Perez‐Concha, Anthony Nguyen, Vicki Bennett, & Louisa Jorm. (2022). Hierarchical label-wise attention transformer model for explainable ICD coding. Journal of Biomedical Informatics. 133. 104161–104161. 20 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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