F. Liu

814 total citations
10 papers, 74 citations indexed

About

F. Liu is a scholar working on Biomedical Engineering, Surgery and Rheumatology. According to data from OpenAlex, F. Liu has authored 10 papers receiving a total of 74 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Biomedical Engineering, 4 papers in Surgery and 4 papers in Rheumatology. Recurrent topics in F. Liu's work include Osteoarthritis Treatment and Mechanisms (4 papers), Radiomics and Machine Learning in Medical Imaging (3 papers) and Medical Imaging and Analysis (3 papers). F. Liu is often cited by papers focused on Osteoarthritis Treatment and Mechanisms (4 papers), Radiomics and Machine Learning in Medical Imaging (3 papers) and Medical Imaging and Analysis (3 papers). F. Liu collaborates with scholars based in United States, Germany and China. F. Liu's co-authors include Lorenzo Nardo, Thomas Baum, J.A. Lynch, Ursula Heilmeier, M.C. Nevitt, Beñat Mallavia, Mark R. Looney, Dean Sheppard, Valentina Pedoia and Jae Ho Sohn and has published in prestigious journals such as Journal of The Electrochemical Society, International Journal of Radiation Oncology*Biology*Physics and American Journal of Transplantation.

In The Last Decade

F. Liu

10 papers receiving 69 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
F. Liu United States	5	48	42	30	11	6	10	74
R. Prada González Spain	5	60 1.3×	16 0.4×	22 0.7×	18 1.6×	26 4.3×	10	81
Roser Tuneu Spain	3	81 1.7×	107 2.5×	62 2.1×	6 0.5×	16 2.7×	4	134
J. Vallø Denmark	3	30 0.6×	84 2.0×	6 0.2×	5 0.5×	15 2.5×	3	99
Rodrigo Luppino Assad Brazil	5	18 0.4×	79 1.9×	10 0.3×	9 0.8×	61 10.2×	12	106
Urvi Karamchandani United Kingdom	5	19 0.4×	14 0.3×	10 0.3×	3 0.3×	3 0.5×	8	52
Ásbjörn Jónsson Sweden	4	63 1.3×	56 1.3×	8 0.3×	37 3.4×	30 5.0×	7	107
Azhar Khan United Kingdom	4	38 0.8×	12 0.3×	15 0.5×	3 0.3×		7	54
Matthieu Ollivier France	10	241 5.0×	23 0.5×	33 1.1×	2 0.2×	28 4.7×	21	254
Mitsunori Ishikawa Japan	6	17 0.4×	18 0.4×	17 0.6×	53 4.8×	7 1.2×	8	78
Kentaro Takeuchi Japan	6	145 3.0×	29 0.7×	30 1.0×		6 1.0×	6	195

Countries citing papers authored by F. Liu

Since Specialization

Citations

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

Fields of papers citing papers by F. Liu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of F. Liu

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

10 of 10 papers shown

Mallavia, Beñat, F. Liu, Simon J. Cleary, et al.. (2021). Natural Killer Cells Recognize Pulmonary Epithelial Stress Molecules during Primary Graft Dysfunction. The Journal of Heart and Lung Transplantation. 40(4). S147–S147. 2 indexed citations

Liu, F., et al.. (2020). Semi-supervised graph-based deep learning for multi-modal prediction of knee osteoarthritis incidence. Osteoarthritis and Cartilage. 28. S305–S306. 6 indexed citations

Schacky, Claudio E. von, Jae Ho Sohn, Sarah C. Foreman, et al.. (2020). Development and performance comparison with radiologists of a multitask deep learning model for severity grading of hip osteoarthritis features on radiographs. Osteoarthritis and Cartilage. 28. S306–S308. 4 indexed citations

Schacky, Claudio E. von, F. Liu, Sarah C. Foreman, et al.. (2019). Automated severity grading of radiographic hip osteoarthritis features with deep learning. Osteoarthritis and Cartilage. 27. S396–S397. 1 indexed citations

Liu, F., et al.. (2019). Discovering knee osteoarthritis bone shape features using deep learning. Osteoarthritis and Cartilage. 27. S386–S387. 3 indexed citations

Huttunen‐Saarivirta, Elina, Pauliina Rajala, Leena Carpén, et al.. (2019). Response to Comments on E. Huttunen-Saarivirta et al., “Kinetic Properties of the Passive Film on Copper in the Presence of Sulfate-Reducing Bacteria” [J. Electrochem. Soc., 165, C450 (2018)]. Journal of The Electrochemical Society. 166(10). Y17–Y26. 5 indexed citations

Schacky, Claudio E. von, F. Liu, Eugene Ozhinsky, et al.. (2019). Artificial Intelligence to Grade Hip Osteoarthritis Features on Radiographs. Seminars in Musculoskeletal Radiology. 1 indexed citations

Sun, Ying, Li Lin, Qi Dou, et al.. (2018). Development and Validation of A Deep Learning Algorithm for Automated Delineation of Primary Tumor for Nasopharyngeal Carcinoma from Multimodal Magnetic Resonance Images. International Journal of Radiation Oncology*Biology*Physics. 102(3). e330–e331. 1 indexed citations

Mallavia, Beñat, F. Liu, Dean Sheppard, & Mark R. Looney. (2015). Inhibiting Integrin αvβ5 Reduces Ischemia–Reperfusion Injury in an Orthotopic Lung Transplant Model in Mice. American Journal of Transplantation. 16(4). 1306–1311. 12 indexed citations

10.

Nevitt, M.C., Ursula Heilmeier, Lorenzo Nardo, et al.. (2015). A reference database of cartilage 3 T MRI T2 values in knees without diagnostic evidence of cartilage degeneration: data from the osteoarthritis initiative. Osteoarthritis and Cartilage. 23(6). 897–905. 39 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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