Sidong Liu

4.4k total citations · 2 hit papers
130 papers, 2.7k citations indexed

About

Sidong Liu is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence. According to data from OpenAlex, Sidong Liu has authored 130 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 42 papers in Computer Vision and Pattern Recognition, 42 papers in Radiology, Nuclear Medicine and Imaging and 34 papers in Artificial Intelligence. Recurrent topics in Sidong Liu's work include AI in cancer detection (25 papers), Radiomics and Machine Learning in Medical Imaging (24 papers) and Image Retrieval and Classification Techniques (21 papers). Sidong Liu is often cited by papers focused on AI in cancer detection (25 papers), Radiomics and Machine Learning in Medical Imaging (24 papers) and Image Retrieval and Classification Techniques (21 papers). Sidong Liu collaborates with scholars based in Australia, China and United States. Sidong Liu's co-authors include Weidong Cai, Dagan Feng, Ron Kikinis, Sonia Pujol, Michael Fulham, Siqi Liu, Antonio Di Ieva, Siqi Liu, ADNI ADNI and Enrico Coiera and has published in prestigious journals such as Proceedings of the National Academy of Sciences, SHILAP Revista de lepidopterología and Nano Letters.

In The Last Decade

Sidong Liu

123 papers receiving 2.6k 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.

Multimodal Neuroimaging Feature Learning for Multiclass Diagnosis of Alzheimer's Disease

2014 404 citations Sidong Liu, Weidong Cai et al. profile →
Early diagnosis of Alzheimer's disease with deep learning

2014 329 citations Siqi Liu, Sidong Liu et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Sidong Liu Australia	28	808	681	623	601	313	130	2.7k
M. Iqbal Saripan Malaysia	30	960 1.2×	712 1.0×	1.2k 1.9×	280 0.5×	60 0.2×	176	3.2k
Paul Bentley United Kingdom	35	541 0.7×	336 0.5×	371 0.6×	411 0.7×	219 0.7×	113	4.4k
Ali R. Khan Canada	29	1.1k 1.3×	282 0.4×	603 1.0×	186 0.3×	329 1.1×	174	3.0k
Siping Chen China	37	1.1k 1.4×	1.5k 2.2×	1.1k 1.7×	252 0.4×	90 0.3×	271	4.9k
Manhua Liu China	31	571 0.7×	889 1.3×	999 1.6×	1.2k 2.0×	785 2.5×	103	3.5k
Fahmi Khalifa United States	26	1.4k 1.7×	517 0.8×	831 1.3×	224 0.4×	68 0.2×	153	2.5k
Joel E.W. Koh Singapore	29	877 1.1×	399 0.6×	437 0.7×	190 0.3×	101 0.3×	61	2.9k
Kai Ma China	27	764 0.9×	717 1.1×	730 1.2×	135 0.2×	53 0.2×	118	2.5k
Roger Tam Canada	25	867 1.1×	297 0.4×	416 0.7×	376 0.6×	249 0.8×	115	2.2k
Mingxia Liu China	19	377 0.5×	430 0.6×	348 0.6×	452 0.8×	249 0.8×	44	1.6k

Countries citing papers authored by Sidong Liu

Since Specialization

Citations

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

Fields of papers citing papers by Sidong Liu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sidong Liu

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

20 of 20 papers shown

1.

Ieva, Antonio Di, et al.. (2025). Meta transfer learning for brain tumor segmentation using nnUNet in meningioma and metastasis cases. Scientific Reports. 15(1). 37599–37599.

2.

Liu, Sidong, Cristián Castillo-Olea, & Shlomo Berkovsky. (2024). Emerging Applications and Translational Challenges for AI in Healthcare. Information. 15(2). 90–90. 1 indexed citations

3.

Liu, Sidong, et al.. (2024). Use of Artificial Intelligence in the Prediction of Chiari Malformation Type 1 Recurrence After Posterior Fossa Decompressive Surgery. Cureus. 16(5). e60879–e60879. 2 indexed citations

4.

Liu, Sidong, et al.. (2024). Meta-Transfer Learning for Few-Shot Meningioma Segmentation. UNSWorks (University of New South Wales, Sydney, Australia). 1–4. 1 indexed citations

5.

Liu, Sidong, Carlo Russo, Eric Suero Molina, & Antonio Di Ieva. (2024). Artificial Intelligence Methods. Advances in experimental medicine and biology. 1462. 21–38. 3 indexed citations

6.

Liu, Sidong, et al.. (2023). Attention-based Deep Learning Approaches in Brain Tumor Image Analysis: A Mini Review. SHILAP Revista de lepidopterología. 12. 164–164. 6 indexed citations

7.

Davidson, Jennilee M., Stephanie L. Rayner, Sidong Liu, et al.. (2023). Inter-Regional Proteomic Profiling of the Human Brain Using an Optimized Protein Extraction Method from Formalin-Fixed Tissue to Identify Signaling Pathways. International Journal of Molecular Sciences. 24(5). 4283–4283. 4 indexed citations

8.

Rapti, Zoi, Jesús Cuevas–Maraver, Eirini Kontou, et al.. (2023). The Role of Mobility in the Dynamics of the COVID-19 Epidemic in Andalusia. Bulletin of Mathematical Biology. 85(6). 54–54. 6 indexed citations

9.

Molina, Eric Suero, et al.. (2023). Radiomics and Machine Learning in Brain Tumors and Their Habitat: A Systematic Review. Cancers. 15(15). 3845–3845. 33 indexed citations

10.

Coiera, Enrico & Sidong Liu. (2022). Evidence synthesis, digital scribes, and translational challenges for artificial intelligence in healthcare. Cell Reports Medicine. 3(12). 100860–100860. 32 indexed citations

11.

Quiroz, Juan C., You‐Zhen Feng, Dana Rezazadegan, et al.. (2021). Development and Validation of a Machine Learning Approach for Automated Severity Assessment of COVID-19 Based on Clinical and Imaging Data: Retrospective Study. JMIR Medical Informatics. 9(2). e24572–e24572. 34 indexed citations

12.

Xiong, Hao, Shlomo Berkovsky, Mia Romano, et al.. (2021). Prediction of anxiety disorders using a feature ensemble based bayesian neural network. Journal of Biomedical Informatics. 123. 103921–103921. 9 indexed citations

13.

Liu, Sidong, Tiebao Meng, Carlo Russo, et al.. (2021). Brain volumetric and fractal analysis of synthetic MRI: A comparative study with conventional 3D T1-weighted images. European Journal of Radiology. 141. 109782–109782. 11 indexed citations

14.

Gao, Yang, Xiong Xiao, Bangcheng Han, et al.. (2020). Deep Learning Methodology for Differentiating Glioma Recurrence From Radiation Necrosis Using Multimodal Magnetic Resonance Imaging: Algorithm Development and Validation (Preprint). 1 indexed citations

15.

Gao, Yang, Xiong Xiao, Bangcheng Han, et al.. (2020). Deep Learning Methodology for Differentiating Glioma Recurrence From Radiation Necrosis Using Multimodal Magnetic Resonance Imaging: Algorithm Development and Validation. JMIR Medical Informatics. 8(11). e19805–e19805. 28 indexed citations

16.

Meneses, Sarah Rúbia Ferreira de, Adam P. Goode, Amanda E. Nelson, et al.. (2016). Clinical algorithms to aid osteoarthritis guideline dissemination. Osteoarthritis and Cartilage. 24(9). 1487–1499. 43 indexed citations

17.

Liu, Sidong, Weidong Cai, Siqi Liu, et al.. (2015). Multimodal neuroimaging computing: the workflows, methods, and platforms. Brain Informatics. 2(3). 181–195. 21 indexed citations

18.

Liu, Sidong, Weidong Cai, Lingfeng Wen, & Dagan Feng. (2012). Semantic-word-based image retrieval for neurodegenerative disorders. 53(19). 2309–5633. 2 indexed citations

19.

Ost, Tobias W. B., Sidong Liu, & Simon Daff. (2011). Cytochrome P450 BM3, NO binding and real-time NO detection. Nitric Oxide. 25(2). 89–94. 2 indexed citations

20.

Liu, Sidong, et al.. (2010). A robust volumetric feature extraction approach for 3D neuroimaging retrieval. PubMed. 2010. 5657–5660. 10 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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