Bo Fu

915 total citations
32 papers, 591 citations indexed

About

Bo Fu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Bo Fu has authored 32 papers receiving a total of 591 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 8 papers in Computer Vision and Pattern Recognition and 6 papers in Signal Processing. Recurrent topics in Bo Fu's work include AI in cancer detection (8 papers), Radiomics and Machine Learning in Medical Imaging (4 papers) and Biometric Identification and Security (4 papers). Bo Fu is often cited by papers focused on AI in cancer detection (8 papers), Radiomics and Machine Learning in Medical Imaging (4 papers) and Biometric Identification and Security (4 papers). Bo Fu collaborates with scholars based in China, Canada and Pakistan. Bo Fu's co-authors include Pei Liu, Simon X. Yang, Ling Deng, Guanzhou Qiu, Hongbo Zhou, Hong Zheng, Rubing Zhang, Xiaorong Zhong, Jianping Li and Chaorong Li and has published in prestigious journals such as Scientific Reports, Expert Systems with Applications and IEEE Access.

In The Last Decade

Bo Fu

30 papers receiving 568 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Bo Fu China 14 179 161 122 116 98 32 591
Qianqian Yang China 21 410 2.3× 74 0.5× 168 1.4× 38 0.3× 172 1.8× 88 1.5k
Niyazi Kılıç Türkiye 13 220 1.2× 46 0.3× 175 1.4× 20 0.2× 75 0.8× 29 506
Hansong Wang China 17 71 0.4× 54 0.3× 47 0.4× 11 0.1× 44 0.4× 40 810
Maciej Kusy Poland 12 188 1.1× 91 0.6× 55 0.5× 7 0.1× 36 0.4× 25 496
Cheng Ju China 15 153 0.9× 30 0.2× 83 0.7× 14 0.1× 63 0.6× 37 704
Yu Bao China 16 320 1.8× 124 0.8× 48 0.4× 170 1.5× 9 0.1× 35 1.1k
Yuwen Li China 18 503 2.8× 85 0.5× 241 2.0× 25 0.2× 19 0.2× 53 1.1k
Oteng Tabona Botswana 3 179 1.0× 20 0.1× 37 0.3× 16 0.1× 24 0.2× 6 523
Banyatsang Mphago Botswana 4 182 1.0× 20 0.1× 33 0.3× 16 0.1× 24 0.2× 5 524
Xinyu Lin China 13 155 0.9× 77 0.5× 250 2.0× 7 0.1× 293 3.0× 58 773

Countries citing papers authored by Bo Fu

Since Specialization
Citations

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

Fields of papers citing papers by Bo Fu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bo Fu

This figure shows the co-authorship network connecting the top 25 collaborators of Bo Fu. A scholar is included among the top collaborators of Bo Fu 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 Fu. Bo Fu 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.
Fu, Bo, et al.. (2025). Predictive modeling for durability characteristics of blended cement concrete utilizing machine learning algorithms. Case Studies in Construction Materials. 22. e04209–e04209. 3 indexed citations
2.
Liu, Yan, et al.. (2024). Effect of tempering process on the structure and properties of M51/X32 bimetal band saw blade. Journal of Physics Conference Series. 2879(1). 12006–12006.
3.
Fu, Bo & Xiao Ding. (2024). A 75.4–102.4-GHz Power Amplifier With 27.7−dB Gain and 16.9% PAE in 65-nm CMOS. IEEE Microwave and Wireless Technology Letters. 35(2). 213–216. 1 indexed citations
4.
Liu, Pei, Luping Ji, Feng Ye, & Bo Fu. (2023). AdvMIL: Adversarial multiple instance learning for the survival analysis on whole-slide images. Medical Image Analysis. 91. 103020–103020. 22 indexed citations
5.
Liu, Pei, et al.. (2023). DSCA: A dual-stream network with cross-attention on whole-slide image pyramids for cancer prognosis. Expert Systems with Applications. 227. 120280–120280. 21 indexed citations
6.
Liu, Pei, Luping Ji, Feng Ye, & Bo Fu. (2023). GraphLSurv: A scalable survival prediction network with adaptive and sparse structure learning for histopathological whole-slide images. Computer Methods and Programs in Biomedicine. 231. 107433–107433. 9 indexed citations
7.
Liu, Shuhui, Bo Fu, Wen Wang, Mei Liu, & Xin Sun. (2022). Dynamic Sepsis Prediction for Intensive Care Unit Patients Using XGBoost-Based Model With Novel Time-Dependent Features. IEEE Journal of Biomedical and Health Informatics. 26(8). 4258–4269. 17 indexed citations
8.
Zhong, Xiaorong, Ting Luo, Ling Deng, et al.. (2020). Multidimensional Machine Learning Personalized Prognostic Model in an Early Invasive Breast Cancer Population-Based Cohort in China: Algorithm Validation Study. JMIR Medical Informatics. 8(11). e19069–e19069. 10 indexed citations
9.
Liu, Pei, Bo Fu, Simon X. Yang, et al.. (2020). Optimizing Survival Analysis of XGBoost for Ties to Predict Disease Progression of Breast Cancer. IEEE Transactions on Biomedical Engineering. 68(1). 148–160. 95 indexed citations
10.
Yang, Libo, Bo Fu, Yan Li, et al.. (2020). Prediction model of the response to neoadjuvant chemotherapy in breast cancers by a Naive Bayes algorithm. Computer Methods and Programs in Biomedicine. 192. 105458–105458. 18 indexed citations
11.
Liu, Pei, Bo Fu, & Simon X. Yang. (2019). HitBoost: Survival Analysis via a Multi-Output Gradient Boosting Decision Tree Method. IEEE Access. 7. 56785–56795. 7 indexed citations
12.
Qiu, Yan, Liya Wang, Xiaorong Zhong, et al.. (2019). A multiple breast cancer stem cell model to predict recurrence of T1–3, N0 breast cancer. BMC Cancer. 19(1). 729–729. 11 indexed citations
13.
Fu, Bo, Pei Liu, Jie Lin, et al.. (2018). Predicting Invasive Disease-Free Survival for Early Stage Breast Cancer Patients Using Follow-Up Clinical Data. IEEE Transactions on Biomedical Engineering. 66(7). 2053–2064. 47 indexed citations
14.
Qiu, Hang, Haiyan Yu, Liya Wang, et al.. (2017). Electronic Health Record Driven Prediction for Gestational Diabetes Mellitus in Early Pregnancy. Scientific Reports. 7(1). 16417–16417. 53 indexed citations
15.
16.
Chen, Xin, Bo Fu, Yong He, & Min Wu. (2014). Timesharing-tracking framework for decentralized reinforcement learning in fully cooperative multi-agent system. IEEE/CAA Journal of Automatica Sinica. 1(2). 127–133. 8 indexed citations
17.
Li, Chaorong, et al.. (2013). Rapid-transform based rotation invariant descriptor for texture classification under non-ideal conditions. Pattern Recognition. 47(1). 313–325. 14 indexed citations
18.
Fu, Bo, et al.. (2012). TEXTURE-BASED FINGERPRINT RECOGNITION COMBINING DIRECTIONAL FILTER BANKS AND WAVELET. International Journal of Pattern Recognition and Artificial Intelligence. 26(4). 1256012–1256012. 5 indexed citations
19.
Fu, Bo, et al.. (2012). Analysis of multi-biometric encryption at feature-level fusion. 3546. 4563–4567. 1 indexed citations
20.
Fu, Bo, et al.. (2007). Isolation of a strain of Acidithiobacillus caldus and its role in bioleaching of chalcopyrite. World Journal of Microbiology and Biotechnology. 23(9). 1217–1225. 40 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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