Feng Chu

742 total citations
9 papers, 484 citations indexed

About

Feng Chu is a scholar working on Molecular Biology, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Feng Chu has authored 9 papers receiving a total of 484 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 3 papers in Artificial Intelligence and 2 papers in Computer Vision and Pattern Recognition. Recurrent topics in Feng Chu's work include Machine Learning in Bioinformatics (4 papers), Bioinformatics and Genomic Networks (4 papers) and Gene expression and cancer classification (4 papers). Feng Chu is often cited by papers focused on Machine Learning in Bioinformatics (4 papers), Bioinformatics and Genomic Networks (4 papers) and Gene expression and cancer classification (4 papers). Feng Chu collaborates with scholars based in Singapore and China. Feng Chu's co-authors include Lipo Wang, Wei Xie, Nina Zhou, Lipo Wang, Xiuju Fu, Kok Seng Chua, Hao Liu, Zhiqing Li, Shengli Lu and Hongwei Li and has published in prestigious journals such as Fuzzy Sets and Systems, IEEE/ACM Transactions on Computational Biology and Bioinformatics and International Journal of Neural Systems.

In The Last Decade

Feng Chu

8 papers receiving 449 citations

Peers

Countries citing papers authored by Feng Chu

Since Specialization

Citations

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

Fields of papers citing papers by Feng Chu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Feng Chu

This figure shows the co-authorship network connecting the top 25 collaborators of Feng Chu. A scholar is included among the top collaborators of Feng Chu 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 Feng Chu. Feng Chu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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9 of 9 papers shown

#	Work	Indexed citations
1	Arrhythmia Classifier Using a Layer-wise Quantized Convolutional Neural Network for Resource-Constrained Devices 2020 ·Zhiqing Li, Hongwei Li, (unknown), Feng Chu, Shengli Lu, Hao Liu	7
2	Extracting very simple diagnostic rules from microarray data 2010 ·PubMed ·Lipo Wang, Feng Chu	3
3	A General Wrapper Approach to Selection of Class-Dependent Features 2008 ·IEEE Transactions on Neural Networks ·Lipo Wang, Nina Zhou, Feng Chu	92
4	Accurate Cancer Classification Using Expressions of Very Few Genes 2007 ·IEEE/ACM Transactions on Computational Biology and Bioinformatics ·Lipo Wang, Feng Chu, Wei Xie	198
5	APPLICATIONS OF SUPPORT VECTOR MACHINES TO CANCER CLASSIFICATION WITH MICROARRAY DATA 2005 ·International Journal of Neural Systems ·Feng Chu, Lipo Wang	130
6	A fuzzy neural network for intelligent data processing 2005 ·Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE ·Wei Xie, Feng Chu, Lipo Wang, (unknown)	0
7	Training RBF neural networks on unbalanced data 2004 ·Xiuju Fu, Lipo Wang, Kok Seng Chua, Feng Chu	19
8	Gene selection and cancer classification using a fuzzy neural network 2004 ·Feng Chu, Wei Xie, Lipo Wang	24
9	Quantitative evaluation of university teaching quality — an application of fuzzy set and approximate reasoning 1990 ·Fuzzy Sets and Systems ·Feng Chu	11

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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