Ying-Jen Lin

548 total citations
16 papers, 344 citations indexed

About

Ying-Jen Lin is a scholar working on Cancer Research, Surgery and Pathology and Forensic Medicine. According to data from OpenAlex, Ying-Jen Lin has authored 16 papers receiving a total of 344 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Cancer Research, 11 papers in Surgery and 7 papers in Pathology and Forensic Medicine. Recurrent topics in Ying-Jen Lin's work include Breast Cancer Treatment Studies (14 papers), Breast Implant and Reconstruction (11 papers) and Breast Lesions and Carcinomas (7 papers). Ying-Jen Lin is often cited by papers focused on Breast Cancer Treatment Studies (14 papers), Breast Implant and Reconstruction (11 papers) and Breast Lesions and Carcinomas (7 papers). Ying-Jen Lin collaborates with scholars based in Taiwan, Singapore and Switzerland. Ying-Jen Lin's co-authors include Hung‐Wen Lai, Shou‐Tung Chen, Shou‐Jen Kuo, Shih-Lung Lin, Dar-Ren Chen, Chi Wei Mok, Hwa‐Koon Wu, Dar‐Ren Chen, Chih‐Jung Chen and Chuan‐Cheng Wang and has published in prestigious journals such as PLoS ONE, Annals of Surgery and Medicine.

In The Last Decade

Ying-Jen Lin

15 papers receiving 342 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ying-Jen Lin Taiwan 11 293 221 100 34 34 16 344
Sabatino D’Archi Italy 9 149 0.5× 161 0.7× 81 0.8× 65 1.9× 20 0.6× 34 240
Federica Chiesa Italy 8 215 0.7× 203 0.9× 125 1.3× 43 1.3× 13 0.4× 18 293
Anne Bodilsen Denmark 9 148 0.5× 208 0.9× 103 1.0× 115 3.4× 28 0.8× 18 283
Daniela Ochoa United States 7 212 0.7× 176 0.8× 90 0.9× 120 3.5× 11 0.3× 15 283
K.A.J. von Smitten Finland 10 268 0.9× 244 1.1× 161 1.6× 129 3.8× 17 0.5× 14 385
Ragheed Al Mufti United Kingdom 9 189 0.6× 142 0.6× 97 1.0× 36 1.1× 15 0.4× 14 300
Sankaran Narayanan United Kingdom 8 144 0.5× 99 0.4× 39 0.4× 31 0.9× 10 0.3× 25 209
James Mansell United Kingdom 10 213 0.7× 246 1.1× 118 1.2× 111 3.3× 21 0.6× 19 370
Emily M. Clarke-Pearson United States 8 261 0.9× 83 0.4× 35 0.3× 162 4.8× 10 0.3× 16 342
Martin Furmanski Switzerland 6 108 0.4× 212 1.0× 175 1.8× 52 1.5× 25 0.7× 6 293

Countries citing papers authored by Ying-Jen Lin

Since Specialization
Citations

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

Fields of papers citing papers by Ying-Jen Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ying-Jen Lin. 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 Ying-Jen Lin. The network helps show where Ying-Jen Lin may publish in the future.

Co-authorship network of co-authors of Ying-Jen Lin

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

All Works

16 of 16 papers shown
1.
Lai, Hung‐Wen, Joseph Lin, Ying-Jen Lin, et al.. (2023). Oncoplastic and reconstructive breast surgeon performance and impact on breast reconstructions: Clinical outcomes, learning curve, and patients’ satisfaction. Surgical Oncology. 47. 101920–101920. 6 indexed citations
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Lai, Hung‐Wen, Dar-Ren Chen, Liang‐Chih Liu, et al.. (2023). Robotic Versus Conventional or Endoscopic-assisted Nipple-sparing Mastectomy and Immediate Prosthesis Breast Reconstruction in the Management of Breast Cancer. Annals of Surgery. 279(1). 138–146. 21 indexed citations
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Lai, Hung‐Wen, Shou‐Tung Chen, Ying-Jen Lin, et al.. (2021). Minimal Access (Endoscopic and Robotic) Breast Surgery in the Surgical Treatment of Early Breast Cancer—Trend and Clinical Outcome From a Single-Surgeon Experience Over 10 Years. Frontiers in Oncology. 11. 739144–739144. 28 indexed citations
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Lai, Hung‐Wen, Chuan‐Cheng Wang, Chih‐Jung Chen, et al.. (2018). The learning curve of robotic nipple sparing mastectomy for breast cancer: An analysis of consecutive 39 procedures with cumulative sum plot. European Journal of Surgical Oncology. 45(2). 125–133. 55 indexed citations
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Lai, Hung‐Wen, Yuting Wu, Chih‐Jung Chen, et al.. (2018). Clinicopathologic factors related to surgical margin involvement, reoperation, and residual cancer in primary operable breast cancer – An analysis of 2050 patients. European Journal of Surgical Oncology. 44(11). 1725–1735. 30 indexed citations
13.
Wu, Yuting, Wen-Pei Wu, Chih‐Jung Chen, et al.. (2017). Role of breast magnetic resonance imaging in predicting malignant invasion of the nipple-areolar complex. Medicine. 96(28). e7170–e7170. 10 indexed citations
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Lin, Ying-Jen, et al.. (2016). The diagnostic utility of preoperative breast magnetic resonance imaging (MRI) and/or intraoperative sub-nipple biopsy in nipple-sparing mastectomy. European Journal of Surgical Oncology. 43(1). 76–84. 29 indexed citations
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Lai, Hung‐Wen, Chih‐Jung Chen, Ying-Jen Lin, et al.. (2016). Does Breast Magnetic Resonance Imaging Combined With Conventional Imaging Modalities Decrease the Rates of Surgical Margin Involvement and Reoperation?. Medicine. 95(22). e3810–e3810. 20 indexed citations
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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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2026