Yao‐Chin Wang

1.5k total citations · 1 hit paper
46 papers, 994 citations indexed

About

Yao‐Chin Wang is a scholar working on Electrical and Electronic Engineering, Surgery and Neurology. According to data from OpenAlex, Yao‐Chin Wang has authored 46 papers receiving a total of 994 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Electrical and Electronic Engineering, 8 papers in Surgery and 5 papers in Neurology. Recurrent topics in Yao‐Chin Wang's work include Advanced Memory and Neural Computing (5 papers), Thin-Film Transistor Technologies (3 papers) and Industrial Vision Systems and Defect Detection (3 papers). Yao‐Chin Wang is often cited by papers focused on Advanced Memory and Neural Computing (5 papers), Thin-Film Transistor Technologies (3 papers) and Industrial Vision Systems and Defect Detection (3 papers). Yao‐Chin Wang collaborates with scholars based in Taiwan, United States and Slovakia. Yao‐Chin Wang's co-authors include Yu‐Chuan Li, Chieh-Chen Wu, Md. Mohaimenul Islam, Hsuan‐Chia Yang, Tahmina Nasrin Poly, Wen‐Shan Jian, Phung‐Anh Nguyen, Min‐Huei Hsu, Woon‐Man Kung and Phụng Anh Nguyễn and has published in prestigious journals such as Spine, Optics Express and Frontiers in Immunology.

In The Last Decade

Yao‐Chin Wang

41 papers receiving 963 citations

Hit Papers

Misleading Health-Related Information Promoted Through Vi... 2013 2026 2017 2021 2013 50 100 150 200 250

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yao‐Chin Wang Taiwan 14 163 144 128 125 123 46 994
Jihad S. Obeid United States 25 300 1.8× 57 0.4× 247 1.9× 111 0.9× 95 0.8× 84 1.9k
Miguel Ángel Mayer Spain 18 281 1.7× 136 0.9× 139 1.1× 100 0.8× 260 2.1× 75 1.1k
Carlos Luís Parra-Calderón Spain 17 284 1.7× 76 0.5× 107 0.8× 92 0.7× 52 0.4× 80 1.0k
Giang Hai Ha Vietnam 18 185 1.1× 89 0.6× 97 0.8× 167 1.3× 37 0.3× 42 1.2k
Edward Meinert United Kingdom 20 486 3.0× 94 0.7× 224 1.8× 89 0.7× 85 0.7× 89 1.7k
Barbara Barry United States 17 182 1.1× 69 0.5× 185 1.4× 106 0.8× 57 0.5× 53 1.2k
Markus A. Feufel Germany 16 228 1.4× 98 0.7× 72 0.6× 40 0.3× 47 0.4× 72 738
Jiancheng Ye United States 16 249 1.5× 48 0.3× 86 0.7× 64 0.5× 59 0.5× 52 792
Irene Dankwa‐Mullan United States 17 281 1.7× 53 0.4× 215 1.7× 48 0.4× 67 0.5× 60 1.1k

Countries citing papers authored by Yao‐Chin Wang

Since Specialization
Citations

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

Fields of papers citing papers by Yao‐Chin Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yao‐Chin Wang. 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 Yao‐Chin Wang. The network helps show where Yao‐Chin Wang may publish in the future.

Co-authorship network of co-authors of Yao‐Chin Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Yao‐Chin Wang. A scholar is included among the top collaborators of Yao‐Chin Wang 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 Yao‐Chin Wang. Yao‐Chin Wang 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
3.
Islam, Md. Mohaimenul, et al.. (2025). Explainable machine learning model incorporating social determinants of health to predict chronic kidney disease in type 2 diabetes patients. Journal of Diabetes & Metabolic Disorders. 24(1). 115–115. 1 indexed citations
4.
Wu, Chieh-Chen, et al.. (2023). Proton Pump Inhibitors and Risk of Chronic Kidney Disease: Evidence from Observational Studies. Journal of Clinical Medicine. 12(6). 2262–2262. 12 indexed citations
5.
Wang, Yao‐Chin, Chieh-Chen Wu, Abel Po‐Hao Huang, Po‐Chun Hsieh, & Woon‐Man Kung. (2022). Combination of Acupoints for Alzheimer’s Disease: An Association Rule Analysis. Frontiers in Neuroscience. 16. 872392–872392. 7 indexed citations
6.
Yin, Tsung‐Cheng, Adam M. Wegner, Meng-Ling Lu, et al.. (2021). Do Orthopedic Surgeons or Neurosurgeons Detect More Hip Disorders in Patients with Hip-Spine Syndrome? A Nationwide Database Study. Brain Sciences. 11(4). 485–485. 1 indexed citations
7.
Ningrum, Dina Nur Anggraini, Woon‐Man Kung, I‐Shiang Tzeng, et al.. (2021). A Deep Learning Model to Predict Knee Osteoarthritis Based on Nonimage Longitudinal Medical Record. Journal of Multidisciplinary Healthcare. Volume 14. 2477–2485. 12 indexed citations
8.
Ningrum, Dina Nur Anggraini, Sheng‐Po Yuan, Woon‐Man Kung, et al.. (2021). Deep Learning Classifier with Patient’s Metadata of Dermoscopic Images in Malignant Melanoma Detection. Journal of Multidisciplinary Healthcare. Volume 14. 877–885. 39 indexed citations
9.
Tzeng, I‐Shiang, Chou‐Chin Lan, Jau‐Yuan Chen, et al.. (2020). <p>Age, Period and Cohort Analysis of Rates of Emergency Department Visits Due to Pneumonia in Taiwan, 1998–2012</p>. Risk Management and Healthcare Policy. Volume 13. 1459–1466. 1 indexed citations
10.
Wu, Chieh-Chen, Md. Mohaimenul Islam, Tahmina Nasrin Poly, et al.. (2019). An artificial intelligence approach to early predict non-ST-elevation myocardial infarction patients with chest pain. Computer Methods and Programs in Biomedicine. 173. 109–117. 51 indexed citations
11.
Wu, Chieh-Chen, Hsuan‐Chia Yang, Phụng Anh Nguyễn, et al.. (2018). Levothyroxine use and the risk of breast cancer: a nation-wide population-based case–control study. Archives of Gynecology and Obstetrics. 298(2). 389–396. 7 indexed citations
12.
Wang, Yao‐Chin, et al.. (2018). Patient satisfaction with dermatology teleconsultation by using MedX. Computer Methods and Programs in Biomedicine. 167. 37–42. 28 indexed citations
13.
Wang, Yao‐Chin, et al.. (2017). The use of surface electromyography in dysphagia evaluation. Technology and Health Care. 25(5). 1025–1028. 6 indexed citations
14.
Wei, Cheng‐Yu, et al.. (2016). Cardiac Autonomic Function in Patients With Ankylosing Spondylitis. Medicine. 95(21). e3749–e3749. 8 indexed citations
15.
Iqbal, Usman, Phụng Anh Nguyễn, Richard Lu, et al.. (2016). Cancer-disease associations: A visualization and animation through medical big data. Computer Methods and Programs in Biomedicine. 127. 44–51. 26 indexed citations
16.
Wei, Cheng‐Yu, et al.. (2015). Obstructive hydrocephalus as a result of giant cell tumor of the thoracic spine: A case report. Oncology Letters. 11(1). 39–44. 1 indexed citations
17.
Wang, Yao‐Chin & Bor‐Shyh Lin. (2014). An Optomechatronics Inspection Technique of TFT Array Flaw Applied to Medical Display. IEEE/ASME Transactions on Mechatronics. 20(1). 321–326. 3 indexed citations
18.
Lin, Muh-Shi, et al.. (2013). Seat Belt Syndrome With Cauda Equina Syndrome. Spine. 38(25). E1624–E1627. 2 indexed citations
19.
Syed-Abdul, Shabbir, Luis Fernández-Luque, Wen‐Shan Jian, et al.. (2013). Misleading Health-Related Information Promoted Through Video-Based Social Media: Anorexia on YouTube. Journal of Medical Internet Research. 15(2). e30–e30. 252 indexed citations breakdown →
20.
Kung, Woon‐Man, Kuo-Sheng Hung, Wen‐Ta Chiu, et al.. (2010). Quantitative assessment of impaired postevacuation brain re-expansion in bilateral chronic subdural haematoma: Possible mechanism of the higher recurrence rate. Injury. 43(5). 598–602. 41 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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