Yung-Fu Chen

1.6k total citations
61 papers, 968 citations indexed

About

Yung-Fu Chen is a scholar working on Computer Vision and Pattern Recognition, Cardiology and Cardiovascular Medicine and Artificial Intelligence. According to data from OpenAlex, Yung-Fu Chen has authored 61 papers receiving a total of 968 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Computer Vision and Pattern Recognition, 11 papers in Cardiology and Cardiovascular Medicine and 10 papers in Artificial Intelligence. Recurrent topics in Yung-Fu Chen's work include Machine Learning in Healthcare (5 papers), Sexual function and dysfunction studies (4 papers) and Heart Rate Variability and Autonomic Control (4 papers). Yung-Fu Chen is often cited by papers focused on Machine Learning in Healthcare (5 papers), Sexual function and dysfunction studies (4 papers) and Heart Rate Variability and Autonomic Control (4 papers). Yung-Fu Chen collaborates with scholars based in Taiwan, China and United States. Yung-Fu Chen's co-authors include Tan-Hsu Tan, Hsuan‐Hung Lin, Yung‐Kuan Chan, Wei‐Sheng Chung, Munkhjargal Gochoo, Chia‐Hung Kao, Cheng‐Li Lin, J.S. Taur, Tsu‐Yi Hsieh and Meng-Hsiun Tsai and has published in prestigious journals such as Scientific Reports, Sensors and Information Sciences.

In The Last Decade

Yung-Fu Chen

60 papers receiving 924 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Yung-Fu Chen Taiwan	19	236	168	129	111	102	61	968
Esko Alasaarela Finland	19	174 0.7×	127 0.8×	283 2.2×	90 0.8×	134 1.3×	68	1.0k
Zhi‐Ri Tang China	20	150 0.6×	203 1.2×	111 0.9×	41 0.4×	50 0.5×	62	1.1k
Marco A. Gutiérrez Brazil	19	106 0.4×	103 0.6×	263 2.0×	46 0.4×	123 1.2×	157	1.6k
Baek Hwan Cho South Korea	18	84 0.4×	171 1.0×	176 1.4×	85 0.8×	123 1.2×	50	1.1k
Łukasz Kidziński United States	20	175 0.7×	138 0.8×	444 3.4×	28 0.3×	35 0.3×	44	1.5k
Yujun Li China	15	206 0.9×	209 1.2×	81 0.6×	23 0.2×	125 1.2×	143	1.0k
Kaijian Xia China	19	399 1.7×	401 2.4×	128 1.0×	28 0.3×	64 0.6×	94	1.3k
S. M. Reza Soroushmehr United States	20	572 2.4×	505 3.0×	252 2.0×	176 1.6×	63 0.6×	95	1.8k
Narendra D. Londhe India	25	256 1.1×	438 2.6×	151 1.2×	129 1.2×	284 2.8×	125	1.9k

Countries citing papers authored by Yung-Fu Chen

Since Specialization

Citations

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

Fields of papers citing papers by Yung-Fu Chen

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yung-Fu Chen

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

All Works

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20 of 20 papers shown

Liu, Cheng‐Wei, et al.. (2023). Left ventricular hypertrophy detection using electrocardiographic signal. Scientific Reports. 13(1). 2556–2556. 17 indexed citations

Tan, Tan-Hsu, et al.. (2020). Designing a clinical decision support system to predict readmissions for patients admitted with all-cause conditions. Journal of Ambient Intelligence and Humanized Computing. 6 indexed citations

Gochoo, Munkhjargal, Tan-Hsu Tan, Shih-Chia Huang, et al.. (2019). Novel IoT-Based Privacy-Preserving Yoga Posture Recognition System Using Low-Resolution Infrared Sensors and Deep Learning. IEEE Internet of Things Journal. 6(4). 7192–7200. 81 indexed citations

Lin, Hsuan‐Hung, et al.. (2018). A Web-Based Decision Support System for Predicting Readmission of Pneumonia Patients after Discharge. 24. 2305–2310. 6 indexed citations

Lee, Ming‐Huei, et al.. (2018). Health Education and Symptom Flare Management Using a Video-based m-Health System for Caring Women With IC/BPS. Urology. 119. 62–69. 22 indexed citations

Lin, Hsuan‐Hung, et al.. (2017). Decision Support Systems for Predicting Erectile Dysfunction. 1 indexed citations

Chen, Yung-Fu, et al.. (2017). Bronchiectasis and increased risk of ischemic stroke: a nationwide population-based cohort study. International Journal of COPD. Volume 12. 1375–1383. 19 indexed citations

Lin, Chih-Sheng, et al.. (2016). Guidelines for reducing image retakes of general digital radiography. Advances in Mechanical Engineering. 8(4). 30 indexed citations

Hsu, Shih‐Kuang, et al.. (2016). Enhancing the bioactivity of yttria-stabilized zirconia immobilized with adhesive peptide using l-dopa as cross-linker. Thin Solid Films. 620. 145–149. 3 indexed citations

10.

Pham, Tuan D., et al.. (2015). Measures of Morphological Complexity of Gray Matter on Magnetic Resonance Imaging for Control Age Grouping. Entropy. 17(12). 8130–8151. 5 indexed citations

11.

Lu, Chunfeng, et al.. (2015). Design of a Computer-Assisted System to Automatically Detect Cell Types Using ANA IIF Images for the Diagnosis of Autoimmune Diseases. Journal of Medical Systems. 39(10). 314–314. 3 indexed citations

12.

Tseng, Chien-Ming, et al.. (2012). Evaluation of stock trading performance of students using a web-based virtual stock trading system. Computers & Mathematics with Applications. 64(5). 1495–1505. 6 indexed citations

13.

Lin, Hsuan‐Hung, et al.. (2012). Disulfide Bonding Pattern Prediction Server Based on Normalized Pair Distance by MODELLER. 290. 581–584. 4 indexed citations

14.

Chen, Yung-Fu, et al.. (2009). True color image steganography using palette and minimum spanning tree. 273–278. 7 indexed citations

15.

Lin, Hsuan‐Hung, et al.. (2008). Application of wavelet decomposition and gradient variation in texture image retrieval. 176(3). 299–304. 5 indexed citations

16.

Lin, Hsuan‐Hung, et al.. (2008). Implementation of an image retrieval system using wavelet decomposition and gradient variation. WSEAS Transactions on Computers archive. 7(6). 724–734. 4 indexed citations

17.

Semmlow, John L., et al.. (2007). Saccadic Behavior during the Response to Pure Vergence Stimuli I: General Properties. Journal of Eye Movement Research. 1(2). 23 indexed citations

18.

Hsu, Yuan-Nian, et al.. (2006). Implementation of a central laboratory with consolidated laboratory network for central Taiwan national hospital union. 181–185. 1 indexed citations

19.

Chen, Yung-Fu, Tainsong Chen, & John L. Semmlow. (2004). Decomposition of Control Signals for Saccade and Vergence Eye Movements Using Independent Component Analysis. Journal of Medical and Biological Engineering. 24(1). 23–28. 1 indexed citations

20.

Chen, Yung-Fu, et al.. (1998). Quantification Analysis for Saccadic Eye Movements. Annals of Biomedical Engineering. 26(6). 1065–1071. 11 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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