Jhen‐Bin Lin

628 total citations
32 papers, 477 citations indexed

About

Jhen‐Bin Lin is a scholar working on Oncology, Obstetrics and Gynecology and Physiology. According to data from OpenAlex, Jhen‐Bin Lin has authored 32 papers receiving a total of 477 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Oncology, 11 papers in Obstetrics and Gynecology and 11 papers in Physiology. Recurrent topics in Jhen‐Bin Lin's work include Endometrial and Cervical Cancer Treatments (11 papers), Nutrition and Health in Aging (9 papers) and Cancer survivorship and care (5 papers). Jhen‐Bin Lin is often cited by papers focused on Endometrial and Cervical Cancer Treatments (11 papers), Nutrition and Health in Aging (9 papers) and Cancer survivorship and care (5 papers). Jhen‐Bin Lin collaborates with scholars based in Taiwan and United States. Jhen‐Bin Lin's co-authors include Jie Lee, Yu-Jen Chen, Ya‐Ting Jan, Meng‐Hao Wu, Fang‐Ju Sun, Chih‐Long Chang, Shih‐Ming Hsu, Chih-Long Chang, Yu‐Jen Chen and Małgorzata Marjańska and has published in prestigious journals such as NeuroImage, Neurology and Scientific Reports.

In The Last Decade

Jhen‐Bin Lin

30 papers receiving 474 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jhen‐Bin Lin Taiwan 14 210 137 130 130 89 32 477
Jie Lee Taiwan 17 312 1.5× 157 1.1× 188 1.4× 155 1.2× 78 0.9× 34 640
Meng‐Hao Wu Taiwan 12 147 0.7× 141 1.0× 136 1.0× 116 0.9× 29 0.3× 18 390
Puy Garrastachu Spain 10 147 0.7× 18 0.1× 39 0.3× 63 0.5× 168 1.9× 22 499
Tzu Chen Yen Taiwan 11 58 0.3× 28 0.2× 72 0.6× 55 0.4× 76 0.9× 12 389
Benjamin T. Gielda United States 14 18 0.1× 43 0.3× 92 0.7× 57 0.4× 44 0.5× 23 424
David Boyce-Fappiano United States 13 54 0.3× 7 0.1× 80 0.6× 198 1.5× 64 0.7× 43 481
Gian Mauro Sacchetti Italy 9 46 0.2× 26 0.2× 32 0.2× 39 0.3× 137 1.5× 26 293
Yo Kawaguchi Japan 11 89 0.4× 22 0.2× 59 0.5× 70 0.5× 25 0.3× 36 287
Pier Francesco Rambaldi Italy 17 17 0.1× 37 0.3× 62 0.5× 123 0.9× 138 1.6× 45 853
Joseph C. Klink United States 13 54 0.3× 8 0.1× 83 0.6× 157 1.2× 24 0.3× 26 509

Countries citing papers authored by Jhen‐Bin Lin

Since Specialization
Citations

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

Fields of papers citing papers by Jhen‐Bin Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jhen‐Bin 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 Jhen‐Bin Lin. The network helps show where Jhen‐Bin Lin may publish in the future.

Co-authorship network of co-authors of Jhen‐Bin Lin

This figure shows the co-authorship network connecting the top 25 collaborators of Jhen‐Bin Lin. A scholar is included among the top collaborators of Jhen‐Bin 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 Jhen‐Bin Lin. Jhen‐Bin Lin 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.
Lin, Jhen‐Bin, et al.. (2025). Impact of radiation dose to the swallowing organs on death from aspiration pneumonia in oral cavity cancer. Oral Oncology. 164. 107291–107291. 1 indexed citations
2.
Lee, Jie, et al.. (2025). Whole-uterine versus individualized-uterine radiotherapy in locally advanced cervical cancer: clinical outcome and toxicity. International Journal of Gynecological Cancer. 35(5). 101817–101817.
3.
Wu, Yufan, Jhen‐Bin Lin, Yi‐Shing Leu, et al.. (2025). Explainable machine learning for predicting aspiration pneumonia after radiotherapy in oral cavity cancer. Radiotherapy and Oncology. 211. 111066–111066.
4.
Lee, Jie, et al.. (2024). Identifying threshold of CT-defined muscle loss after radiotherapy for survival in oral cavity cancer using machine learning. European Radiology. 35(7). 4289–4299. 4 indexed citations
5.
Jan, Ya‐Ting, et al.. (2024). Interpretable machine learning model based on clinical factors for predicting muscle radiodensity loss after treatment in ovarian cancer. Supportive Care in Cancer. 32(8). 544–544. 4 indexed citations
6.
Lin, Jhen‐Bin, et al.. (2024). Thresholds of Body Composition Changes Associated with Survival During Androgen Deprivation Therapy in Prostate Cancer. European Urology Open Science. 70. 99–108. 1 indexed citations
7.
Chang, Chih‐Long, et al.. (2023). Explainable machine learning model for predicting skeletal muscle loss during surgery and adjuvant chemotherapy in ovarian cancer. Journal of Cachexia Sarcopenia and Muscle. 14(5). 2044–2053. 24 indexed citations
8.
Lee, Jie, et al.. (2023). Impact of reduced margin pelvic radiotherapy on gastrointestinal toxicity and outcome in gynecological cancer. Clinical and Translational Radiation Oncology. 43. 100671–100671. 4 indexed citations
9.
Lee, Jie, Jhen‐Bin Lin, Tze-Chien Chen, et al.. (2022). Progressive Skeletal Muscle Loss After Surgery and Adjuvant Radiotherapy Impact Survival Outcomes in Patients With Early Stage Cervical Cancer. Frontiers in Nutrition. 8. 773506–773506. 13 indexed citations
10.
Lee, Jie, Jhen‐Bin Lin, Chih‐Long Chang, et al.. (2022). Optimal prophylactic para-aortic radiotherapy in locally advanced cervical cancer: anatomy-based versus margin-based delineation. International Journal of Gynecological Cancer. 32(5). 606–612. 4 indexed citations
11.
Lin, Hsuan-Yu, Sheng‐Hung Wang, Po‐Ju Lin, et al.. (2021). Low cardiac dose and neutrophil-to-lymphocyte ratio predict overall survival in inoperable esophageal squamous cell cancer patients after chemoradiotherapy. Scientific Reports. 11(1). 6644–6644. 6 indexed citations
12.
Lee, Jie, Jhen‐Bin Lin, Meng‐Hao Wu, et al.. (2021). Association of bowel radiation dose-volume with skeletal muscle loss during pelvic intensity-modulated radiotherapy in cervical cancer. Supportive Care in Cancer. 29(9). 5497–5505. 9 indexed citations
13.
Chiu, Allen Wen-Hsiang, et al.. (2021). Muscle Loss During Androgen Deprivation Therapy Is Associated With Higher Risk of Non-Cancer Mortality in High-Risk Prostate Cancer. Frontiers in Oncology. 11. 722652–722652. 20 indexed citations
14.
Lin, Jhen‐Bin, Ching‐Yuan Cheng, Yu‐An Chien, et al.. (2019). Prognostic significance of lung radiation dose in patients with esophageal cancer treated with neoadjuvant chemoradiotherapy. Radiation Oncology. 14(1). 85–85. 17 indexed citations
15.
Lee, Jie, et al.. (2018). Skeletal Muscle Loss Is an Imaging Biomarker of Outcome after Definitive Chemoradiotherapy for Locally Advanced Cervical Cancer. Clinical Cancer Research. 24(20). 5028–5036. 66 indexed citations
16.
17.
Lee, Jie, et al.. (2018). The Effect of Body Mass Index and Weight Change on Late Gastrointestinal Toxicity in Locally Advanced Cervical Cancer Treated With Intensity-modulated Radiotherapy. International Journal of Gynecological Cancer. 28(7). 1377–1386. 20 indexed citations
18.
19.
Lee, Jie, Jhen‐Bin Lin, Fang‐Ju Sun, et al.. (2017). Safety and efficacy of semiextended field intensity-modulated radiation therapy and concurrent cisplatin in locally advanced cervical cancer patients. Medicine. 96(10). e6158–e6158. 21 indexed citations
20.
Wengenack, Thomas M., Denise A. Reyes, Geoffry L. Curran, et al.. (2010). Regional differences in MRI detection of amyloid plaques in AD transgenic mouse brain. NeuroImage. 54(1). 113–122. 33 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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