Chi-Yu Yang

689 total citations
20 papers, 562 citations indexed

About

Chi-Yu Yang is a scholar working on Cardiology and Cardiovascular Medicine, Artificial Intelligence and Epidemiology. According to data from OpenAlex, Chi-Yu Yang has authored 20 papers receiving a total of 562 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Cardiology and Cardiovascular Medicine, 6 papers in Artificial Intelligence and 4 papers in Epidemiology. Recurrent topics in Chi-Yu Yang's work include Machine Learning in Healthcare (4 papers), Biomedical Text Mining and Ontologies (3 papers) and Adipokines, Inflammation, and Metabolic Diseases (3 papers). Chi-Yu Yang is often cited by papers focused on Machine Learning in Healthcare (4 papers), Biomedical Text Mining and Ontologies (3 papers) and Adipokines, Inflammation, and Metabolic Diseases (3 papers). Chi-Yu Yang collaborates with scholars based in Taiwan and United States. Chi-Yu Yang's co-authors include Pachaiyappan Rajamalli, Pei-Yun Huang, Parthasarathy Gandeepan, Li‐Kang Chu, Hao‐Wu Lin, Chien‐Hong Cheng, N. Senthilkumar, Min‐Jie Huang, Kuo‐Liong Chien and Yuan‐Teh Lee and has published in prestigious journals such as Journal of the American Chemical Society, Arteriosclerosis Thrombosis and Vascular Biology and Atherosclerosis.

In The Last Decade

Chi-Yu Yang

19 papers receiving 553 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Chi-Yu Yang Taiwan 9 347 290 69 46 37 20 562
Yu-Chun Lee Taiwan 8 214 0.6× 217 0.7× 25 0.4× 14 0.3× 15 0.4× 17 392
Ping Shi United States 14 143 0.4× 88 0.3× 18 0.3× 173 3.8× 6 0.2× 24 624
Shao-Ming Yang Taiwan 8 219 0.6× 89 0.3× 42 0.6× 7 0.2× 98 2.6× 38 331
Shaopeng Gu United States 8 215 0.6× 107 0.4× 35 0.5× 99 2.2× 137 3.7× 10 403
Jun Okuno Japan 13 434 1.3× 226 0.8× 15 0.2× 217 4.7× 29 0.8× 29 720
Shaobo Wang China 10 35 0.1× 46 0.2× 16 0.2× 27 0.6× 10 0.3× 24 378
Cao Cai China 4 305 0.9× 212 0.7× 4 0.1× 115 2.5× 49 1.3× 7 499
Yu‐Chieh Cheng Taiwan 12 47 0.1× 62 0.2× 25 0.4× 29 0.6× 4 0.1× 18 383
Yuqi Wang China 11 102 0.3× 80 0.3× 18 0.3× 30 0.7× 6 0.2× 33 400
Xueqi Hu China 11 68 0.2× 77 0.3× 19 0.3× 29 0.6× 4 0.1× 26 360

Countries citing papers authored by Chi-Yu Yang

Since Specialization
Citations

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

Fields of papers citing papers by Chi-Yu Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chi-Yu Yang. 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 Chi-Yu Yang. The network helps show where Chi-Yu Yang may publish in the future.

Co-authorship network of co-authors of Chi-Yu Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Chi-Yu Yang. A scholar is included among the top collaborators of Chi-Yu Yang 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 Chi-Yu Yang. Chi-Yu Yang 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.
Chu, Yuan-Chia, Feipei Lai, Kuan‐Chih Chen, et al.. (2022). Training a Deep Contextualized Language Model for International Classification of Diseases, 10th Revision Classification via Federated Learning: Model Development and Validation Study. JMIR Medical Informatics. 10(11). e41342–e41342. 8 indexed citations
2.
Chen, Kuan‐Chih, et al.. (2022). Automatic International Classification of Diseases Coding System: Deep Contextualized Language Model With Rule-Based Approaches. JMIR Medical Informatics. 10(6). e37557–e37557. 8 indexed citations
3.
Chen, Li‐Chin, Feipei Lai, Cheng-Wei Lü, et al.. (2022). Predicting Postoperative Mortality With Deep Neural Networks and Natural Language Processing: Model Development and Validation. JMIR Medical Informatics. 10(5). e38241–e38241. 14 indexed citations
4.
Kuo, Lu-Cheng, et al.. (2021). Automatic ICD-10 Coding and Training System: Deep Neural Network Based on Supervised Learning. JMIR Medical Informatics. 9(8). e23230–e23230. 43 indexed citations
5.
Lin, Hsien-chin, Chi-Yu Yang, Hung-yi Lee, & Lin-shan Lee. (2018). Domain Independent Key Term Extraction from Spoken Content Based on Context and Term Location Information in the Utterances. 6044–6048.
6.
7.
Yang, Chi-Yu, et al.. (2017). Seeing and hearing too: Audio representation for video captioning. 5. 381–388. 4 indexed citations
8.
Rajamalli, Pachaiyappan, N. Senthilkumar, Parthasarathy Gandeepan, et al.. (2015). A New Molecular Design Based on Thermally Activated Delayed Fluorescence for Highly Efficient Organic Light Emitting Diodes. Journal of the American Chemical Society. 138(2). 628–634. 372 indexed citations
9.
Jiang, Bernard C., et al.. (2013). An SPC-Based Forward-Backward Algorithm for Arrhythmic Beat Detection and Classification. Industrial Engineering & Management Systems. 12(4). 380–388. 2 indexed citations
10.
Yang, Chi-Yu, Ai‐Hsien Li, Wen‐Po Chuang, et al.. (2012). Detection of Asymptomatic Paroxysmal Atrial Fibrillation with the Trans-Telephonic Electrocardiograph System. Telemedicine Journal and e-Health. 18(3). 193–197. 1 indexed citations
11.
Li, Ai‐Hsien, et al.. (2010). Two-Year Follow-Up of Tirofiban-Based Management of Non-ST-Elevation Acute Coronary Syndrome-A Single Center Study. Zhōnghuá mínguó xīnzàngxué huì zázhì. 26(1). 19–27. 2 indexed citations
12.
Lai, Chao‐Lun, et al.. (2008). The Application of Oxygen Saturation of Central Venous Blood (ScVO 2 ) in Complicated Acute Coronary Syndrome as a Probable Disease Monitor A Pilot Study. 2 indexed citations
13.
Yeh, Jia‐Rong, et al.. (2008). Diagnosing Dangerous Arrhythmia Of Patients By Automatic Detecting Of Qrs Complexes In Ecg. Zenodo (CERN European Organization for Nuclear Research). 2 indexed citations
14.
Chien, Kuo‐Liong, Hsiu‐Ching Hsu, Ta‐Chen Su, Chi-Yu Yang, & Yuan‐Teh Lee. (2003). Consistency of genetic inheritance mode and heritability patterns of triglyceride vs. high density lipoprotein cholesterol ratio in two Taiwanese family samples. BMC Genetics. 4(1). 7–7. 27 indexed citations
15.
Chien, Kuo‐Liong, Chi-Yu Yang, & Yuan‐Teh Lee. (2003). Major gene effects in systolic and diastolic blood pressure in families receiving a health examination in Taiwan. Journal of Hypertension. 21(1). 73–79. 13 indexed citations
16.
Huang, Zei‐Shung, Kuo‐Liong Chien, Chi-Yu Yang, et al.. (2003). Peripheral differential leukocyte counts and subsequent mortality from all diseases, cancers, and cardiovascular diseases in Taiwanese.. PubMed. 102(11). 775–81. 19 indexed citations
17.
Chien, Kuo‐Liong, et al.. (1999). Prevalence, awareness, efficiency of control, and target organ damage in Taiwanese patients with hypertension. 1 indexed citations
18.
Huang, Zei‐Shung, Chiu‐Hwa Wang, Ping‐Keung Yip, Chi-Yu Yang, & Ti‐Kai Lee. (1998). F016 In hypercholesterolemia, lower peripheral monocyte count is unique among the major predictors of atherosclerosis. Atherosclerosis. 136. S50–S50. 1 indexed citations
19.
Huang, Zei‐Shung, Chiu‐Hwa Wang, Ping‐Keung Yip, Chi-Yu Yang, & Ti‐Kai Lee. (1996). In Hypercholesterolemia, Lower Peripheral Monocyte Count Is Unique Among the Major Predictors of Atherosclerosis. Arteriosclerosis Thrombosis and Vascular Biology. 16(2). 256–261. 27 indexed citations
20.
Chen, Ming-Fong, Chi-Yu Yang, Wen‐Jone Chen, et al.. (1995). A double-blind comparison of once-daily metoprolol controlled-release and atenolol in the treatment of Chinese patients with mild to moderate hypertension. Cardiovascular Drugs and Therapy. 9(3). 401–406. 2 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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