Yi‐Ting Hwang

1.4k total citations
66 papers, 1.0k citations indexed

About

Yi‐Ting Hwang is a scholar working on Oncology, Statistics and Probability and Surgery. According to data from OpenAlex, Yi‐Ting Hwang has authored 66 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Oncology, 12 papers in Statistics and Probability and 10 papers in Surgery. Recurrent topics in Yi‐Ting Hwang's work include Global Cancer Incidence and Screening (7 papers), Statistical Methods in Clinical Trials (6 papers) and Statistical Distribution Estimation and Applications (6 papers). Yi‐Ting Hwang is often cited by papers focused on Global Cancer Incidence and Screening (7 papers), Statistical Methods in Clinical Trials (6 papers) and Statistical Distribution Estimation and Applications (6 papers). Yi‐Ting Hwang collaborates with scholars based in Taiwan, United States and South Korea. Yi‐Ting Hwang's co-authors include Jeanne S. Mandelblatt, Jack Hadley, Julia H. Rowland, Jane C. Weeks, Hui‐Ling Lee, Ta‐Chen Su, Chien‐Yu Lin, Karen Gold, Melissa Figueiredo and Jennifer Cullen and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Yi‐Ting Hwang

59 papers receiving 1.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yi‐Ting Hwang Taiwan 17 383 208 136 128 125 66 1.0k
Jamie C. Sergeant United Kingdom 25 436 1.1× 83 0.4× 86 0.6× 153 1.2× 82 0.7× 79 1.6k
Yueping Shen China 24 306 0.8× 140 0.7× 146 1.1× 97 0.8× 74 0.6× 97 1.8k
Susanne Strohmaier Austria 18 201 0.5× 267 1.3× 166 1.2× 106 0.8× 52 0.4× 55 1.3k
Mandi Yu United States 17 570 1.5× 96 0.5× 103 0.8× 182 1.4× 114 0.9× 44 1.1k
Nigel Fleeman United Kingdom 23 186 0.5× 59 0.3× 106 0.8× 75 0.6× 116 0.9× 61 1.3k
Iftekhar Khan United Kingdom 19 344 0.9× 118 0.6× 92 0.7× 73 0.6× 137 1.1× 49 1.3k
Joan Largent United States 24 491 1.3× 316 1.5× 356 2.6× 54 0.4× 63 0.5× 58 1.5k
Kirsi Talala Finland 18 190 0.5× 198 1.0× 164 1.2× 272 2.1× 94 0.8× 78 1.3k
Sarah B. Peskoe United States 23 209 0.5× 316 1.5× 216 1.6× 95 0.7× 38 0.3× 83 1.5k
Theresa Shao United States 12 764 2.0× 384 1.8× 89 0.7× 143 1.1× 185 1.5× 30 1.8k

Countries citing papers authored by Yi‐Ting Hwang

Since Specialization
Citations

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

Fields of papers citing papers by Yi‐Ting Hwang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yi‐Ting Hwang. 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 Yi‐Ting Hwang. The network helps show where Yi‐Ting Hwang may publish in the future.

Co-authorship network of co-authors of Yi‐Ting Hwang

This figure shows the co-authorship network connecting the top 25 collaborators of Yi‐Ting Hwang. A scholar is included among the top collaborators of Yi‐Ting Hwang 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 Yi‐Ting Hwang. Yi‐Ting Hwang 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.
Hang, Jen‐Fan, Min‐Che Tung, Pei‐Yi Chu, et al.. (2025). AI-Driven Logistic Regression Models for Bladder Cancer Prediction: A Pilot Study Quantifying Atypical Urothelial Cells with Cytomorphometric Features. Journal of the American Society of Cytopathology. 14(5). S50–S50.
2.
3.
Hwang, Yi‐Ting, et al.. (2024). Using $B$-Spline Model on Depth Camera Data to Predict Physical Activity Energy Expenditure of Different Levels of Human Exercise. IEEE Transactions on Human-Machine Systems. 54(1). 79–88.
4.
Hsu, Shih‐Chang, Shan‐Yueh Chang, Yi‐Ting Hwang, et al.. (2023). mRNA markers associated with malignant pleural effusion. Scientific Reports. 13(1). 6677–6677. 3 indexed citations
5.
Hwang, Yi‐Ting, Hui‐Ling Lee, Po‐Cheng Chang, et al.. (2021). A Novel Approach for Predicting Atrial Fibrillation Recurrence After Ablation Using Deep Convolutional Neural Networks by Assessing Left Atrial Curved M-Mode Speckle-Tracking Images. Frontiers in Cardiovascular Medicine. 7. 605642–605642. 16 indexed citations
6.
Lee, Ting‐Ting, et al.. (2021). Exploring the Outcomes and Satisfaction of Automated Physiological Monitoring Systems Among Nurses. CIN Computers Informatics Nursing. 40(3). 178–185. 3 indexed citations
7.
Hwang, Yi‐Ting, et al.. (2020). A five-year longitudinal study of the relation between end-stage kidney disease as the outcomes. BMC Nephrology. 21(1). 132–132. 2 indexed citations
8.
Lin, Chien‐Yu, Hui‐Ling Lee, Yi‐Ting Hwang, et al.. (2020). Urinary heavy metals, DNA methylation, and subclinical atherosclerosis. Ecotoxicology and Environmental Safety. 204. 111039–111039. 28 indexed citations
9.
Lin, Shih-Wei, et al.. (2018). Using Nursing Information and Data Mining to Explore the Factors That Predict Pressure Injuries for Patients at the End of Life. CIN Computers Informatics Nursing. 37(3). 133–141. 19 indexed citations
10.
Chou, Chung‐Chuan, Hui‐Ling Lee, Po‐Cheng Chang, et al.. (2018). Left atrial emptying fraction predicts recurrence of atrial fibrillation after radiofrequency catheter ablation. PLoS ONE. 13(1). e0191196–e0191196. 27 indexed citations
11.
Nomura, Sarah, Yi‐Ting Hwang, Scarlett Lin Gomez, et al.. (2017). Dietary intake of soy and cruciferous vegetables and treatment-related symptoms in Chinese-American and non-Hispanic White breast cancer survivors. Breast Cancer Research and Treatment. 168(2). 467–479. 15 indexed citations
12.
Wang, Chun‐Chao, et al.. (2011). A Robust Estimation of the Proportion of True Null Hypotheses Based on a Beta Mixture Model. 49(2). 43–59. 1 indexed citations
13.
Hwang, Yi‐Ting, et al.. (2009). Assessing Multivariate Normality Based on Shapiro-Wilk Test. 47(3). 143–158. 1 indexed citations
14.
Hwang, Yi‐Ting, et al.. (2007). A Remark on the Zhang Omnibus Test for Normality. Journal of Applied Statistics. 34(2). 177–184. 2 indexed citations
15.
Hadley, Jack, Jeanne S. Mandelblatt, Jean M. Mitchell, et al.. (2003). Medicare Breast Surgery Fees and Treatment Received by Older Women with Localized Breast Cancer. Health Services Research. 38(2). 553–573. 28 indexed citations
16.
Hadley, Jack, Daniel Polsky, Jeanne S. Mandelblatt, et al.. (2003). An exploratory instrumental variable analysis of the outcomes of localized breast cancer treatments in a medicare population. Health Economics. 12(3). 171–186. 46 indexed citations
17.
Mandelblatt, Jeanne S., Jon Kerner, Jack Hadley, et al.. (2002). Variations in breast carcinoma treatment in older medicare beneficiaries. Cancer. 95(7). 1401–1414. 128 indexed citations
18.
Liang, Wenchi, Caroline B. Burnett, Julia H. Rowland, et al.. (2002). Communication Between Physicians and Older Women With Localized Breast Cancer: Implications for Treatment and Patient Satisfaction. Journal of Clinical Oncology. 20(4). 1008–1016. 86 indexed citations
19.
Edge, Stephen B., Karen Gold, Christine D. Berg, et al.. (2002). Patient and provider characteristics that affect the use of axillary dissection in older women with Stage I–II breast carcinoma. Cancer. 94(10). 2534–2541. 34 indexed citations
20.
Mandelblatt, Jeanne S., Stephen B. Edge, Neal J. Meropol, et al.. (2002). Sequelae of axillary lymph node dissection in older women with stage 1 and 2 breast carcinoma. Cancer. 95(12). 2445–2454. 31 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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