Luping Fang

607 total citations
34 papers, 397 citations indexed

About

Luping Fang is a scholar working on Biomedical Engineering, Cardiology and Cardiovascular Medicine and Computer Vision and Pattern Recognition. According to data from OpenAlex, Luping Fang has authored 34 papers receiving a total of 397 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Biomedical Engineering, 9 papers in Cardiology and Cardiovascular Medicine and 9 papers in Computer Vision and Pattern Recognition. Recurrent topics in Luping Fang's work include Respiratory Support and Mechanisms (7 papers), Non-Invasive Vital Sign Monitoring (6 papers) and Heart Rate Variability and Autonomic Control (5 papers). Luping Fang is often cited by papers focused on Respiratory Support and Mechanisms (7 papers), Non-Invasive Vital Sign Monitoring (6 papers) and Heart Rate Variability and Autonomic Control (5 papers). Luping Fang collaborates with scholars based in China, Germany and Netherlands. Luping Fang's co-authors include Qing Pan, Gangmin Ning, Fei Lü, Huiqing Ge, Lingwei Zhang, Qiang Gong, Ruofan Wang, Yunfei Lu, Qi Xue and Yanhua Li and has published in prestigious journals such as Expert Systems with Applications, IEEE Access and Sensors.

In The Last Decade

Luping Fang

31 papers receiving 386 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Luping Fang China 10 123 94 81 55 53 34 397
Haixia Yan China 14 112 0.9× 53 0.6× 161 2.0× 31 0.6× 33 0.6× 85 618
Chunming Xia China 14 62 0.5× 31 0.3× 204 2.5× 52 0.9× 63 1.2× 99 662
Rahul Krishnan Pathinarupothi India 11 86 0.7× 21 0.2× 164 2.0× 45 0.8× 49 0.9× 53 500
Riad Taha Al-Kasasbeh Jordan 17 26 0.2× 27 0.3× 129 1.6× 20 0.4× 72 1.4× 68 662
Jamal El Mhamdi Morocco 11 42 0.3× 34 0.4× 43 0.5× 29 0.5× 133 2.5× 48 491
He Wang China 12 37 0.3× 30 0.3× 103 1.3× 3 0.1× 39 0.7× 56 620
Paolo Ciampolini Italy 13 88 0.7× 17 0.2× 264 3.3× 44 0.8× 64 1.2× 48 820
Monika Simjanoska North Macedonia 9 162 1.3× 20 0.2× 178 2.2× 33 0.6× 58 1.1× 32 387

Countries citing papers authored by Luping Fang

Since Specialization
Citations

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

Fields of papers citing papers by Luping Fang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Luping Fang

This figure shows the co-authorship network connecting the top 25 collaborators of Luping Fang. A scholar is included among the top collaborators of Luping Fang 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 Luping Fang. Luping Fang 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
1.
Pan, Qing, Peilun Li, Fei Lü, et al.. (2024). In Silico Design of Heterogeneous Microvascular Trees Using Generative Adversarial Networks and Constrained Constructive Optimization. Microcirculation. 31(5). e12854–e12854.
2.
Zhu, Qiang, Lingwei Zhang, Fei Lü, Luping Fang, & Qing Pan. (2024). Class activation map-based slicing-concatenation and contrastive learning: A novel strategy for record-level atrial fibrillation detection. Expert Systems with Applications. 262. 125619–125619. 1 indexed citations
3.
Wang, Daoyuan, Qing Pan, Molei Yan, et al.. (2023). Reinforcement Learning Model for Managing Noninvasive Ventilation Switching Policy. IEEE Journal of Biomedical and Health Informatics. 27(8). 4120–4130. 2 indexed citations
4.
Wu, Zhefu, et al.. (2023). Robust multimedia recommender system based on dynamic collaborative filtering and directed adversarial learning. International Journal of Machine Learning and Cybernetics. 14(11). 3851–3865. 3 indexed citations
5.
Pan, Qing, et al.. (2022). Comprehensive breathing variability indices enhance the prediction of extubation failure in patients on mechanical ventilation. Computers in Biology and Medicine. 153. 106459–106459. 4 indexed citations
6.
Wu, Zhefu, et al.. (2022). Directional Adversarial Training for Robust Ownership-Based Recommendation System. IEEE Access. 10. 2880–2894. 3 indexed citations
7.
Pan, Qing, Jie Pan, Zhongheng Zhang, Luping Fang, & Huiqing Ge. (2021). Assessment of respiratory system compliance under pressure control ventilation without an inspiratory pause maneuver. Physiological Measurement. 42(8). 08NT01–08NT01. 2 indexed citations
8.
Fang, Luping, et al.. (2021). Ownership Recommendation via Iterative Adversarial Training. Neural Processing Letters. 54(1). 637–655. 5 indexed citations
9.
Pan, Qing, Ruofan Wang, Arata Tabuchi, et al.. (2021). Pulsatility damping in the microcirculation: Basic pattern and modulating factors. Microvascular Research. 139. 104259–104259. 5 indexed citations
10.
Pan, Qing, Lingwei Zhang, Jie Pan, et al.. (2021). An interpretable 1D convolutional neural network for detecting patient-ventilator asynchrony in mechanical ventilation. Computer Methods and Programs in Biomedicine. 204. 106057–106057. 32 indexed citations
11.
Pan, Qing, Lingwei Zhang, Jie Pan, et al.. (2021). Identifying Patient–Ventilator Asynchrony on a Small Dataset Using Image-Based Transfer Learning. Sensors. 21(12). 4149–4149. 17 indexed citations
12.
Ge, Huiqing, Jimei Wang, Lingwei Zhang, et al.. (2020). Risk Factors for Patient–Ventilator Asynchrony and Its Impact on Clinical Outcomes: Analytics Based on Deep Learning Algorithm. Frontiers in Medicine. 7. 597406–597406. 3 indexed citations
13.
Zhang, Lingwei, Siqi Fang, Yunfei Lu, et al.. (2020). Detection of patient-ventilator asynchrony from mechanical ventilation waveforms using a two-layer long short-term memory neural network. Computers in Biology and Medicine. 120. 103721–103721. 46 indexed citations
14.
Pan, Qing, et al.. (2019). Combining Sequence Learning and U-Like-Net for Hippocampus Segmentation. Journal of Computer-Aided Design & Computer Graphics. 31(8). 1382–1382. 3 indexed citations
15.
Pan, Qing, Ruofan Wang, Yihua Yu, et al.. (2016). The degree of heart rate asymmetry is crucial for the validity of the deceleration and acceleration capacity indices of heart rate: A model-based study. Computers in Biology and Medicine. 76. 39–49. 5 indexed citations
16.
Pan, Qing, Ruofan Wang, Guolong Cai, et al.. (2016). Do the deceleration/acceleration capacities of heart rate reflect cardiac sympathetic or vagal activity? A model study. Medical & Biological Engineering & Computing. 54(12). 1921–1933. 27 indexed citations
17.
Fang, Luping, et al.. (2015). Cognitive Effects of Visualization on Learning Data Structure and Algorithms. 70–78. 2 indexed citations
18.
Pan, Qing, Ruofan Wang, Bettina Reglin, et al.. (2014). Simulation of microcirculatory hemodynamics: estimation of boundary condition using particle swarm optimization. Bio-Medical Materials and Engineering. 24(6). 2341–2347. 6 indexed citations
19.
Fang, Luping, et al.. (2013). Research on Internationalization of 3D Slicer. 14. 469–473. 1 indexed citations
20.
Fang, Luping, et al.. (2004). Cooperative multi-agent transport based on coevolution. Society of Instrument and Control Engineers of Japan. 2. 1301–1304. 1 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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